European pilots’ perceptions of safety culture in European ... · European pilots’ perceptions...

European pilots’ perceptions of safety culture in European Aviation T.W.Reader, A. Parand and B. Kirwan

Programme Manager Michel Piers, NLR

Operations Manager Lennaert Speijker, NLR

Project Manager (P5) Barry Kirwan, EUROCONTROL

Grant Agreement No. 640597

Document Identification D5.4

Status Approved

Version 2.0

Classification Public

Future Sky Safety is a Joint Research Programme on Safety, initiated by EREA, the association of European Research

Establishments in Aeronautics. The Programme contains two streams of activities: 1) coordination of the safety research

programmes of the EREA institutes and 2) collaborative research projects on European safety priorities.

This deliverable is produced by the Project P5: Resolving the Organisational Accident of Future Sky Safety. One of P5’s aims

is to spread the successful safety culture approach used in Air Traffic Management to other sectors of the Air Transport

System, including Airlines. This survey of more than 7000 pilots represents a significant step in this direction.

Project: Reference ID: Classification:

Resolving the organizational accident FSS_P5_LSE_D5.4 Public

LSE Status: Approved Issue: 2.0 PAGE 2/180 This document is the property of Future Sky Safety and shall not be distributed or reproduced without the formal approval of Coordinator NLR. Future Sky Safety has received funding from the EU’s Horizon 2020 Research and Innovation Programme, under Grant Agreement No. 640597.

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Contributing partners

Company Name

LSE Tom Reader, Anam Parand

EUROCONTROL Barry Kirwan

Document Change Log

Version No. Issue Date Remarks

1.0 18-11-2016 First formal release

1.1 24-11-2016 Update by NLR (mainly template corrections)

2.0 28-11-2016 Second formal release

Approval status

Prepared by: (name) Company Role Date

Anam Parand LSE Principal Analyst 26-08-2016

Checked by: (name) Company Role Date

Tom Reader LSE WP5.3 Leader 14-11-2016

Approved by: (name) Company Role Date

Barry Kirwan EUROCONTROL Project Manager (P5) 18-11-2016

Lennaert Speijker NLR Operations Manager 28-11-2016




Acronyms

Acronym Definition

ANSP Air Navigation Service Provider

ATM Air Traffic Management

CAA Civil Aviation Authority

EASA The European Aviation Safety Agency

EU The European Union

LSE London School of Economics and Political Science




EXECUTIVE SUMMARY

Problem Area

The aviation industry in Europe has been transformed over recent decades. A combination of global

economic changes, changing customer demands, and increases in airlines with alternate business models has made the industry incredibly competitive. In addition, the nature of regulation has changed, with both

national and European-wide bodies having a role in industry governance.

Nonetheless, European aviation remains an ultra-safe industry with a highly impressive safety record. Due to the low frequency of accidents and near-misses, and the non-linear relationship between profitability

and safety (Madsen 2011), safety culture has become a key indicator for assessing safety practices and

susceptibility to safety problems within aviation organisations.

Safety culture refers to the safety-related norms, values, and practices shared by groups managing risk in

an organisation (Guldenmund 2000). Within European aviation, safety culture is the cornerstone of an

effective safety management system (CAA, 2015), yet within the European aviation industry, there is currently no systematic method or practice of measuring and comparing safety culture amongst pilots.

Description of Work

The aim of this study is to explore perceptions of pilots in Europe on safety culture in their company, and

factors that may affect these perceptions. To address this, the project comprised the following three

stages.

1. The London School of Economics and Political Science (LSE) adapted a psychometrically

established questionnaire tool originally used for measuring safety culture in Air Traffic

Management to pilots based in Europe. Items were tailored to ensure relevance to airlines and pertinent safety culture dimensions were added.

2. An electronic version of the survey was predominantly distributed through the European Cockpit

Association (ECA) promoting the survey to their member associations via newsletters and social media.

3. Trends and variations in safety culture were compared by different organisational and personal

contexts (e.g. type of company worked for, contract type).

Results & Conclusions

A total of 7,239 (14% of the population) commercial pilots in Europe completed the survey. The results show that perceptions of safety culture are generally positive amongst pilots in Europe. However, the

survey also reveals significant differences in pilot’ assessments of safety culture depending factors such as

the type of airlines they work for, or the type of contracts they work to. Pilots working on atypical




contracts, and those working for low cost and cargo airlines, have more negative perceptions of safety

culture than their colleagues working under more secure forms of employment and for network carrier airlines. Perceptions of management commitment to safety, staffing and equipment, fatigue and

perceived organisational support were not especially positive across the whole sample. For example, over

half of the sample of pilots (50.05%) felt that fatigue was not taken seriously within their organisation (while 28.83% neither agreed nor disagreed) and less than 20% agreed that their company cares about

their well-being. On the positive side, almost all pilots (93.49%) agreed that their colleagues are

committed to safety, 88.45% agreed that they read reports of incidents or occurrences relevant to their work, and the large majority (79.08%) felt prepared to speak to their direct manager if an unsafe situation

develops.

Applicability

The report contains important insights for the entire industry, including airlines, regulatory bodies and the

European Commission. Several steps are proposed to ensure that the right lessons can be learned from

the data, and to maintain the industry’s reputation as the safest mode of transport.




TABLE OF CONTENTS

Contributing partners 3 Document Change Log 3 Approval status 3 Acronyms 4

Executive summary 5

Problem Area 5 Description of Work 5 Results & Conclusions 5 Applicability 6

Table of Contents 7

List of Tables 9

List of Figures 11

REPORT SUMMARY 14

Background 15 Method 15 Sample 15 Safety culture results – overview of strengths and weaknesses 17 Safety culture dimensions 21 Safety Culture differences between types of organisation 23 Comparisons of safety culture between companies 25 Comparisons with Air Traffic Management 28 Discussion 29 Conclusions 31

MAIN REPORT 32

1 Introduction 33

1.1. The context 33 1.2. Safety culture: definition and background 33 1.3. Pilot’ perceptions of safety culture in the European Aviation industry: the current study 37 1.4. Objectives 37

2 Methods 38

2.1. Safety culture measurement 38




2.2. Data collection 41 2.3. Study participants 41 2.4. Demographic analysis 41 2.5. Descriptive analysis of survey items 41 2.6. Group comparisons 43 2.7. Comparing responses from participants in different airlines 44

3 Results 45

3.1. Responses 45 3.2. Demographics 45 3.3. Reporting item-by-item 56 3.3.1. Q Section B – Descriptive statistics of all respondents by items in section B of survey 56 3.3.2. Q Section C – Descriptive statistics of all respondents by items in section C 60 3.3.3. Q Section D – Descriptive statistics of all respondents by items in section D 63 3.4. Safety culture dimensions 68 3.4.1. Dimension Descriptive Statistics & Reliability 68 3.4.2. Dimension correlations 70 3.4.3. Between group differences 71 3.4.4. Correlations 135 3.4.5. Comparison with ATM (a comparison with published data) 145

4 Discussion and limitations 146

4.1. Discussion 146 4.2. Limitations 147

5 Conclusions and recommendations 148

5.1. Conclusions 148 5.2. Recommendations 148

6 References 150

7 Appendices 152

7.1. Appendix 1 Demographic group cross-tabulations 152 7.2. Appendix 2 Means for dimensions by demographic groups 156 7.3. Appendix 3 Favourable/Unfavourable Responses by Groups 161




LIST OF TABLES

TABLE 1 PROPORTION OF COMPANY MEAN SCORES BY DIMENSION (FOR COMPANIES WITH =>30 RESPONDENTS) ................ 27 TABLE 2 QUESTIONNAIRE ITEMS & DIMENSIONS .............................................................................................. 39 TABLE 3 STATISTICAL DEFINITIONS ............................................................................................................... 42 TABLE 4: COMPANY DEMOGRAPHICS ............................................................................................................ 45 TABLE 5 PILOTS’ COUNTRY BASE.................................................................................................................. 47 TABLE 6 NATIONALITY OF RESPONDENTS (EXCLUDES NATIONALITIES THAT MAKE UP LESS THAN 1% OF THE SAMPLE) ............ 50 TABLE 7 PILOT DEMOGRAPHICS .................................................................................................................. 51 TABLE 8 SURVEY SECTION B DESCRIPTIVE DATA ............................................................................................... 56 TABLE 9 SURVEY SECTION B FAVOURABLE AND UNFAVOURABLE RESPONSES ............................................................ 57 TABLE 10 SURVEY SECTION C DESCRIPTIVE DATA.............................................................................................. 60 TABLE 11 SURVEY SECTION C FAVOURABLE AND UNFAVOURABLE RESPONSES........................................................... 61 TABLE 12 SURVEY SECTION DESCRIPTIVES: PERCEIVED ORGANISATIONAL SUPPORT (N=6893) ...................................... 63 TABLE 13 SURVEY SECTION D DESCRIPTIVES: FATIGUE (N=6896)......................................................................... 64 TABLE 14 SURVEY SECTION D DESCRIPTIVES: SPEAKING-UP (N=6872) .................................................................. 64 TABLE 15 SURVEY SECTION D DESCRIPTIVES: NATIONAL AUTHORITY (N=6841) ....................................................... 64 TABLE 16 SURVEY SECTION D FAVOURABLE AND UNFAVOURABLE RESPONSES .......................................................... 65 TABLE 17 DIMENSION SCALE DESCRIPTIVE STATISTICS AND RELIABILITY ................................................................... 69 TABLE 18 DIMENSION CORRELATIONS ........................................................................................................... 70 TABLE 19 MEAN SCORES BY COMPANY TYPE ................................................................................................... 73 TABLE 20 ANOVA OVERVIEW OF SIGNIFICANT DIFFERENCES BETWEEN GROUPS FOR COMPANY TYPE ............................... 74 TABLE 21 MEAN SCORES BY JOB TYPE ........................................................................................................... 88 TABLE 22 ANOVA OVERVIEW OF SIGNIFICANT DIFFERENCES BETWEEN GROUPS FOR JOB TITLE ...................................... 89 TABLE 23 MEAN SCORES BY MANAGEMENT ROLE ............................................................................................. 97 TABLE 24 ANOVA OVERVIEW OF SIGNIFICANT DIFFERENCES BETWEEN GROUPS FOR MANAGEMENT ROLE ......................... 98 TABLE 25 MEAN SCORES BY TRAINING BACKGROUND ...................................................................................... 104 TABLE 26 ANOVA OVERVIEW OF SIGNIFICANT DIFFERENCES BETWEEN GROUPS FOR TRAINING BACKGROUND .................. 105 TABLE 27 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY COMPANY ID (FOR COMPANIES WITH =>30 RESPONDENTS)

................................................................................................................................................ 142 TABLE 28 PERCEPTIONS OF SAFETY CULTURE BY NATIONALITY ............................................................................ 143 TABLE 29 PERCEPTIONS OF SAFETY CULTURE BY THE COUNTRY AT WHICH PILOTS ARE BASED. ....................................... 144 TABLE 30 CONTRACT TYPE AND AGE .......................................................................................................... 152 TABLE 31 CONTRACT TYPE AND COMPANY TYPE ............................................................................................ 152 TABLE 32 CONTRACT TYPE AND FLYING EXPERIENCE ....................................................................................... 153 TABLE 33 CONTRACT TYPE AND TRAINING BACKGROUND .................................................................................. 153 TABLE 34 COMPANY TYPE AND TENURE ...................................................................................................... 154 TABLE 35 COMPANY TYPE AND FLYING EXPERIENCE ........................................................................................ 154 TABLE 36 COMPANY TYPE AND TRAINING BACKGROUND .................................................................................. 155




TABLE 37 AGE AND TRAINING BACKGROUND ................................................................................................ 155 TABLE 38 MEANS FOR DIMENSIONS BY DEMOGRAPHIC GROUPS (JOB TITLE; GENDER; FLYING EXPERIENCE; AGE; TENURE) ... 156 TABLE 39 MEANS FOR DIMENSIONS BY DEMOGRAPHIC GROUPS (COMPANY TYPE; CONTRACT TYPE; PART-TIME OR PART YEAR

WORKING; PART-TIMERS AVERAGE PERCENTAGE WORK TIME) ..................................................................... 157 TABLE 40 MEANS FOR DIMENSIONS BY DEMOGRAPHIC GROUPS (MANAGEMENT ROLE; TRAINING BACKGROUND) .............. 158 TABLE 41 MEANS FOR DIMENSIONS BY NATIONALITY (FOR NATIONALITIES WITH =>30 RESPONDENTS) .......................... 159 TABLE 42 MEANS FOR DIMENSIONS BY COUNTRY BASE (FOR COUNTRIES WITH =>30 RESPONDENTS) ............................. 160 TABLE 43 FAVOURABLE/UNFAVOURABLE RESPONSES BY COMPANY TYPE (EXCLUDING OTHER CATEGORY) ....................... 161 TABLE 44 FAVOURABLE/UNFAVOURABLE RESPONSES BY CONTRACT TYPE (EXCLUDING OTHER CATEGORY) ....................... 168 TABLE 45 FAVOURABLE/UNFAVOURABLE RESPONSES BY TRAINING BACKGROUND (EXCLUDING OTHER CATEGORY) ............. 174




LIST OF FIGURES

FIGURE 1 COMPANY TYPE ......................................................................................................................... 16 FIGURE 2 CONTRACT TYPE ........................................................................................................................ 16 FIGURE 3 COUNTRY BASE (THIS FIGURE EXCLUDES COUNTRIES THAT MAKE UP LESS THAN 1 % OF THE SAMPLE) ................... 17 FIGURE 4 TOP 5 MOST FAVOURABLE RESPONSES IN SECTION B ............................................................................. 18 FIGURE 5 TOP 5 LEAST FAVOURABLE RESPONSES OVERALL IN SECTION B .................................................................. 18 FIGURE 6 TOP 5 MOST FAVOURABLE RESPONSES IN SECTION C ............................................................................. 19 FIGURE 7 TOP 5 LEAST FAVOURABLE RESPONSES IN SECTION C ............................................................................. 19 FIGURE 8 TOP 5 MOST FAVOURABLE RESPONSES IN SECTION D ............................................................................. 20 FIGURE 9 TOP 5 LEAST FAVOURABLE RESPONSES IN SECTION D ............................................................................. 20 FIGURE 10 SPIDER GRAPH OF DIMENSION SCALE MEAN SCORES ............................................................................ 22 FIGURE 11 MEANS FOR DIMENSIONS BY COMPANY TYPE .................................................................................... 23 FIGURE 12 MEANS FOR DIMENSIONS BY CONTRACT TYPE ................................................................................... 24 FIGURE 13 MEANS FOR COLLEAGUE COMMITMENT TO SAFETY BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS) ... 25 FIGURE 14 MEANS FOR JUST CULTURE AND REPORTING BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS) ........... 26 FIGURE 15 MEANS FOR STAFF & EQUIPMENT BY COMPANY ID (FOR COMPANIES WITH =>30 RESPONDENTS) .................... 26 FIGURE 16 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY COMPANY ID (FOR COMPANIES WITH =>30 RESPONDENTS)

.................................................................................................................................................. 27 FIGURE 17 COMPARISONS BETWEEN PILOTS AND AIR TRAFFIC CONTROLLERS ............................................................ 28 FIGURE 18 RESPONDENTS PER COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS) .............................................. 46 FIGURE 19 COMPANY TYPE ........................................................................................................................ 47 FIGURE 20 COUNTRY BASE (THIS FIGURE DOES NOT INCLUDE COUNTRIES THAT MAKE UP LESS THAN 1 % OF THE SAMPLE) ...... 48 FIGURE 21 NATIONALITY OF RESPONDENTS (EXCLUDES COUNTRIES THAT MAKE UP LESS THAN 1 % OF THE SAMPLE) ............. 50 FIGURE 22 GENDER ................................................................................................................................ 52 FIGURE 23 JOB TITLE ............................................................................................................................... 52 FIGURE 24 AGE ..................................................................................................................................... 53 FIGURE 25 FLYING EXPERIENCE ................................................................................................................... 53 FIGURE 26 MANAGEMENT ROLE ................................................................................................................. 54 FIGURE 27 TENURE IN COMPANY ................................................................................................................ 54 FIGURE 28 CONTRACT TYPE ....................................................................................................................... 55 FIGURE 29 TRAINING BACKGROUND ............................................................................................................. 55 FIGURE 30 TOP 5 MOST FAVOURABLE RESPONSES IN SECTION B ........................................................................... 58 FIGURE 31 TOP 5 LEAST FAVOURABLE RESPONSES OVERALL IN SECTION B ................................................................ 59 FIGURE 32 TOP 5 MOST FAVOURABLE RESPONSES IN SECTION C ........................................................................... 62 FIGURE 33 TOP 5 LEAST FAVOURABLE RESPONSES IN SECTION C ........................................................................... 63 FIGURE 34 TOP 5 MOST FAVOURABLE RESPONSES IN SECTION D ........................................................................... 66 FIGURE 35 TOP 5 LEAST FAVOURABLE RESPONSES IN SECTION D ........................................................................... 67 FIGURE 36 SPIDER GRAPH OF DIMENSION SCALE MEAN SCORES ............................................................................ 69




FIGURE 37 MEANS AND ERROR BARS FOR ALL DIMENSIONS BY COMPANY TYPE ......................................................... 72 FIGURE 38 MEANS FOR MANAGEMENT COMMITMENT TO SAFETY BY COMPANY TYPE ................................................ 75 FIGURE 39 MEANS FOR COLLABORATION & INVOLVEMENT BY COMPANY TYPE ......................................................... 76 FIGURE 40 MEANS FOR JUST CULTURE BY COMPANY TYPE .................................................................................. 77 FIGURE 41 MEANS FOR COMMUNICATION & LEARNING BY COMPANY TYPE ............................................................. 78 FIGURE 42 MEANS FOR RISK HANDLING BY COMPANY TYPE ................................................................................ 79 FIGURE 43 MEANS FOR COLLEAGUE COMMITMENT BY COMPANY TYPE .................................................................. 80 FIGURE 44 MEANS FOR STAFF & EQUIPMENT BY COMPANY TYPE ......................................................................... 81 FIGURE 45 MEANS FOR FATIGUE BY COMPANY TYPE ......................................................................................... 83 FIGURE 46 MEANS FOR SPEAKING UP BY COMPANY TYPE ................................................................................... 84 FIGURE 47 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY COMPANY TYPE ................................................... 86 FIGURE 48 MEANS AND ERROR BARS FOR ALL DIMENSIONS BY JOB TITLE ................................................................. 87 FIGURE 49 MEANS FOR MANAGEMENT COMMITMENT TO SAFETY BY JOB TITLE ........................................................ 90 FIGURE 50 MEANS FOR COMMUNICATION & LEARNING BY JOB TITLE .................................................................... 91 FIGURE 51 MEANS FOR COLLEAGUE COMMITMENT BY JOB TITLE .......................................................................... 92 FIGURE 52 MEANS FOR STAFF & EQUIPMENT BY JOB TITLE ................................................................................. 93 FIGURE 53 MEANS FOR FATIGUE BY JOB TITLE................................................................................................. 94 FIGURE 54 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY JOB TITLE ........................................................... 95 FIGURE 55 MEANS AND ERROR BARS FOR ALL DIMENSIONS BY MANAGEMENT ROLE ................................................... 96 FIGURE 56 MEANS FOR MANAGEMENT COMMITMENT BY MANAGEMENT ROLE ....................................................... 99 FIGURE 57 MEANS FOR PROCEDURES & TRAINING BY MANAGEMENT ROLE ........................................................... 100 FIGURE 58 MEANS FOR FATIGUE BY MANAGEMENT ROLE ................................................................................ 101 FIGURE 59 MEANS FOR PROCEDURES & TRAINING BY MANAGEMENT ROLE ........................................................... 102 FIGURE 60 MEANS AND ERROR BARS FOR ALL DIMENSIONS BY TRAINING BACKGROUND (OTHER NOT INCLUDED) ............... 103 FIGURE 61 MEANS FOR MANAGEMENT COMMITMENT BY TRAINING BACKGROUND.................................................. 106 FIGURE 62 MEANS FOR COLLABORATION & INVOLVEMENT BY TRAINING BACKGROUND............................................. 107 FIGURE 63 MEANS FOR JUST CULTURE BY TRAINING BACKGROUND ..................................................................... 108 FIGURE 64 MEANS FOR COMMUNICATION & LEARNING BY TRAINING BACKGROUND ................................................ 109 FIGURE 65 RISK HANDLING BY TRAINING BACKGROUND ................................................................................... 110 FIGURE 66 MEANS FOR COLLEAGUE COMMITMENT BY TRAINING BACKGROUND ...................................................... 111 FIGURE 67 MEANS FOR STAFF & EQUIPMENT BY TRAINING BACKGROUND ............................................................. 112 FIGURE 68 MEANS FOR PROCEDURES & TRAINING BY TRAINING BACKGROUND ....................................................... 113 FIGURE 69 MEANS FOR FATIGUE BY TRAINING BACKGROUND ............................................................................ 114 FIGURE 70 MEANS FOR SPEAKING UP BY TRAINING BACKGROUND ...................................................................... 115 FIGURE 71 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY TRAINING BACKGROUND ....................................... 116 FIGURE 72 MEANS AND ERROR BARS FOR ALL DIMENSIONS BY CONTRACT TYPE (OTHER NOT INCLUDED) ......................... 117 FIGURE 73 MEANS FOR MANAGEMENT COMMITMENT BY TYPICAL/ATYPICAL CONTRACT .......................................... 118 FIGURE 74 MEANS FOR COLLABORATION & INVOLVEMENT BY TYPICAL/ATYPICAL CONTRACT ..................................... 119 FIGURE 75 MEANS FOR JUST CULTURE BY TYPICAL/ATYPICAL CONTRACT .............................................................. 119




FIGURE 76 MEANS FOR COMMUNICATION & LEARNING BY TYPICAL/ATYPICAL CONTRACT ......................................... 120 FIGURE 77 MEANS FOR RISK HANDLING BY TYPICAL/ATYPICAL CONTRACT ............................................................ 121 FIGURE 78 MEANS FOR COLLEAGUE COMMITMENT BY TYPICAL/ATYPICAL CONTRACT............................................... 121 FIGURE 79 MEANS FOR STAFF & EQUIPMENT BY TYPICAL/ATYPICAL CONTRACT...................................................... 122 FIGURE 80 MEANS FOR PROCEDURES & TRAINING BY TYPICAL/ATYPICAL CONTRACT................................................ 123 FIGURE 81 MEANS FOR FATIGUE BY TYPICAL/ATYPICAL CONTRACT ..................................................................... 123 FIGURE 82 MEANS FOR SPEAKING UP BY TYPICAL/ATYPICAL CONTRACT ............................................................... 124 FIGURE 83 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY TYPICAL/ATYPICAL CONTRACT................................ 125 FIGURE 84 MEANS AND ERROR BARS FOR ALL DIMENSIONS BY PART-TIME/YEAR & FULL-TIME/YEAR ............................. 126 FIGURE 85 MEANS FOR MANAGEMENT COMMITMENT BY PART-TIME/YEAR AND FULL TIME ....................................... 127 FIGURE 86 MEANS FOR JUST CULTURE BY PART-TIME/YEAR AND FULL TIME .......................................................... 128 FIGURE 87 MEANS FOR COMMUNICATION & LEARNING BY PART-TIME/YEAR AND FULL TIME ..................................... 129 FIGURE 88 MEANS FOR COLLEAGUE COMMITMENT BY PART-TIME/YEAR AND FULL TIME ........................................... 130 FIGURE 89 MEANS FOR STAFF & EQUIPMENT BY PART-TIME/YEAR AND FULL TIME .................................................. 131 FIGURE 90 MEANS FOR FATIGUE BY PART-TIME/YEAR AND FULL TIME ................................................................. 132 FIGURE 91 MEANS FOR SPEAKING UP BY PART-TIME/YEAR AND FULL TIME ........................................................... 133 FIGURE 92 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY PART-TIME/YEAR AND FULL TIME ............................ 134 FIGURE 93 MEANS FOR MANAGEMENT COMMITMENT TO SAFETY BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS)

................................................................................................................................................ 136 FIGURE 94 MEANS FOR COLLABORATION AND INVOLVEMENT BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS) ... 137 FIGURE 95 MEANS FOR JUST CULTURE AND REPORTING BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS) ......... 137 FIGURE 96 MEANS FOR COMMUNICATION AND LEARNING BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS)....... 138 FIGURE 97 MEANS FOR RISK HANDLING BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS) ............................. 138 FIGURE 98 MEANS FOR COLLEAGUE COMMITMENT TO SAFETY BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS) . 139 FIGURE 99 MEANS FOR STAFF & EQUIPMENT BY COMPANY ID (FOR COMPANIES WITH =>30 RESPONDENTS) .................. 139 FIGURE 100 MEANS FOR PROCEDURES AND TRAINING (FOR COMPANIES WITH =>30 RESPONDENTS) ............................ 140 FIGURE 101 MEANS FOR FATIGUE (FOR COMPANIES WITH =>30 RESPONDENTS) .................................................... 140 FIGURE 102 MEANS FOR SPEAKING UP (FOR COMPANIES WITH =>30 RESPONDENTS) .............................................. 141 FIGURE 103 MEANS FOR PERCEIVED ORGANISATIONAL SUPPORT BY COMPANY (FOR COMPANIES WITH =>30 RESPONDENTS)

................................................................................................................................................ 141 FIGURE 104 COMPARISON T-TEST BETWEEN PILOTS AND ATM .......................................................................... 145




REPORT SUMMARY




Background

Safety culture refers to the safety-related norms, values, and practices shared by groups managing risk in

an organisation (Guldenmund 2000). Within European aviation, safety culture is the cornerstone of an effective safety management system (CAA 2015), yet a modest body of research has focussed on

measuring and comparing safety culture as perceived by pilots. To address this, the current study tailored

the EUROCONTROL safety culture survey (used for air traffic control organisations) to pilots. This is a survey that has been psychometrically validated in the European Air Traffic Management industry, and

used to measure and benchmark safety culture in over 25 countries, with over 20,000 respondents. The

survey was administered to pilots working in the European aviation industry. The main purpose was to:

i. Evaluate pilot observations on organisational safety culture within the European aviation industry

ii. Identify areas were the industry is strong, alongside areas for improvement iii. Compare the experiences of pilots in different sectors, organisations, and personal contexts.

Method

An electronic safety culture survey was developed by the London School of Economics and Political

Science (LSE) to pilots working within European aviation. The survey was primarily distributed through the

European Cockpit Association (ECA) promoting the survey to their member associations via newsletters and social media.

Sample

In total, 7,239 valid responses were received, which is roughly equivalent to 14% of commercial pilots

working in Europe and is statistically representative for the European pilot population (with a 95%

confidence level). It should be noted that this high number of respondents makes this the largest safety culture survey of pilots to date in Europe and is a credit to European pilots’ commitment to safety.

Most participants were male (96%), aged between 31-50 (62%), with considerable flying experience (44%

had greater than 10,000 flight hours and 29% over 5001 flight hours). There was a near equal distribution of Captains (56%) to First Officers (43%), with Second Officers constituting 1%. Most pilots (88%) did not

have a managerial role and were trained either through self-funded modular training (42%) or via an

airline funded cadetship (24%). Almost half (48%) of the pilots had been in their company for 11 or more years, only 4% had been in the company for less than a year.

The number of responses greatly varied between the 33 companies. As can be seen in Figure 1, over half

of the sample (55%) worked for a Network (e.g. flag/legacy) carrier and almost a quarter (24%) for a Low Cost airline.




88.47%

11.14%

Typical contract

Atypicalcontract

Other

Figure 1 Company type

As can be seen in Figure 2, the large majority of pilots (88.47%) had a typical (permanent) contract.

Figure 2 Contract type

Typical contract = permanent contract; Atypical contract = Self-employed, Zero hours, Fixed-term, and Pay-to-Fly

contracts.

The figure below demonstrates the countries from which pilots are based. Germany had the most responses (23%). The pilots’ nationalities largely matched the countries where people are based, with

some expected divergence.

2% 6%

7%

2%1%

24%55%

2% Aerialwork/ambulance/surveillanceBusiness

Cargo

Charter/leisure

General Aviation

Helicopter

Low cost

Network

Other (Please state)




2%2% 3%2%

8%

23%

1%3%

4%3%9%

4%

3%

8%

6%

8%

11%

AustriaBelgiumDenmarkFinlandFranceGermanyIcelandIrelandItalyLuxembourgNetherlandsNorwayPortugalSpainSwedenSwitzerlandUnited Kingdom

Figure 3 Country base (This figure excludes countries that make up less than 1 % of the sample)

Safety culture results – overview of strengths and weaknesses

In terms of overall responses to the survey items (including demographic questions), the following

observations can be made. On a scale of 1-5 (with 1 being a highly negative response, and 5 being a highly positive response), the mean average response to all survey items (n=58) was 3.49, and the average

standard deviation was .99 (indicating large variation). For the majority of items (59%), response means

were above 3.5. For 36%, the response means were between 2.5 and 3.5. For 5% of items, response means were below 2.5. This indicates that, overall, participants tended to respond to survey items in a

positive fashion, however there is clear room for improvement, with some groups of pilots showing

negative perceptions of safety culture (e.g. those on atypical contracts) and some survey items/dimensions were responded to in a consistently negative fashion (e.g. fatigue).

In terms of response patterns to individual items, it is useful to focus on whether participants gave a

‘favourable’ or ‘unfavourable’ response to an item within each survey section1.

Section B of the survey presented relatively general questions on how pilots perceived safety culture in

their organization. In terms of response patterns, pilots responded most favourably to the items ‘B01 My

colleagues are committed to safety’ (94% favourable response). It is also noticeable that pilots felt they could speak to their manager if an unsafe situation developed (79%), and that they were encouraged to

voice concerns on safety (79%). The five most favourable responses in section B are reported below. In

this graph, green represents a favourable response, yellow a neutral or ‘not really sure’ response, and orange an unfavourable response.

1 Reverse (negatively) worded items were amended so that the green bar is always a positive answer.




0% 50% 100%

B06 Pilots have a high degree of trust inmanagement with regard to safety.

B03 We have sufficient staff to do our worksafely.

B17 Changes to the company, systems andprocedures are properly assessed for safety risk.

B12 We get timely feedback on the safety issueswe raise.

B16 There is good communication up and downthe company about safety.

Unfavourable

Neither

Favourable

0% 20% 40% 60% 80% 100%

B01 My colleagues are committed to safety.

B26 If I see unsafe behaviour by any of mycolleagues I would talk to them about it.

B07 I have confidence in the people that Iinteract with in my normal working situation.

B02 Voicing concerns about safety isencouraged.

B15 I am prepared to speak to my directmanager when unsafe situations are developing.

Unfavourable

Neither

Favourable

Figure 4 Top 5 most favourable responses in section B

In section B, pilots responded least favourably to the items ‘B06 Pilots have a high degree of trust in

management with regard to safety’ (38% unfavourable). Concerns were also expressed on the sufficiency

of staff to work safely (28% unfavourable). The five least favourable responses in section B are shown below.

Figure 5 Top 5 least favourable responses overall in section B

For section C, which refers to safety culture on the more operational aspects of being a pilot, the most

favourable item was ‘C13 I feel entirely confident to fly my aircraft’ (91.47% favourable). In addition, 82% felt SOPs were appropriate for supporting safe operations, and 81% did not feel they had to take risks that

made them feel uncomfortable about safety.




0% 20% 40% 60% 80% 100%

C13 I feel entirely confident to fly my aircraft.

C02 I read reports of incidents or occurrencesthat are relevant to our work.

C16 I have sufficient training to understand theprocedures associated with my work.

C14 The SOPs associated with my work areappropriate to ensure safe operations.

C10r I have to take risks that make me feeluncomfortable about safety.

Unfavourable

Neither

Favourable

Figure 6 Top 5 most favourable responses in Section C

In section C, pilots responded least favourably to the items ‘C09 Adequate training is provided when new

systems and procedures are introduced’ (38% unfavourable). Concerns were also expressed on whether

maintenance are able to promptly repair technical deficiencies to aircraft (21%), and opportunities for pilots to regularly practice manual flying skills (21%).

Figure 7 Top 5 least favourable responses in Section C

Section D refers to questions on the working life of pilots more generally and how much they feel

supported by their organisation. Here, the most favourable response was to the item ‘D08 Captains encourage their crew to speak-up if they are concerned with decisions made by the Captain’ (80%

favourable response). It is notable that only 46% agreed that their national aviation authority takes safety

seriously.

0% 20% 40% 60% 80% 100%

C09 Adequate training is provided when newsystems and procedures are introduced.

C08 Maintenance are able to promptly repairtechnical deficiencies to the aircraft.

C07 I have sufficient opportunity to regularlypractice my manual flying skills.

C03 We have procedures that are focused onappearing to follow the rules, rather than

improving practice.

C05 I am satisfied with the level of confidentialityof the reporting and investigation process.

Unfavourable

Neither

Favourable




0% 20% 40% 60% 80% 100%

D08 Captains encourage their crew to speak-upif they are concerned with decisions made by

the Captain.

D02 First officers are willing to challengeCaptains on their decision making.

D06 I would feel comfortable to complete afatigue report.

D16r The company would ignore any complaintfrom me.

D07 My national aviation authority takes safetyseriously.

Unfavourable

Neither

Favourable

0% 20% 40% 60% 80% 100%

D01r Pilots in this company are often tired atwork.

D11 The company really cares about mywellbeing.

D14 The company cares about my generalsatisfaction at work.

D15r Even if I did the best job possible, thecompany would fail to notice.

D13r The company fails to appreciate any extraeffort from me.

Unfavourable

Neither

Favourable

Figure 8 Top 5 most favourable responses in section D

The least favourable response in section D related to ‘D01r Pilots in this company are often tired at work’

(58% unfavourable). This means that over half of respondents thought that pilots in their company are

often tired at work. The graph below also highlights that many pilots do not feel cared for by their organisation (e.g. D11).

Figure 9 Top 5 least favourable responses in section D




Safety culture dimensions

Safety culture is a complex concept, with surveys consisting of multiple items referring to various issues.

One of the best ways to make survey results more meaningful and manageable is to break the survey down into its underlying dimensions. The method used in the EUROCONTROL survey is to focus on eight

dimensions that together comprise safety culture. These are listed below, along with three dimensions

(the last three) which were added to tailor the survey for pilots:

Management Commitment to Safety

Collaboration & Involvement

Just Culture & Reporting Communication & Learning

Colleague Commitment to Safety

Risk Handling Staff and Equipment

Procedures & Training

Fatigue Speaking up about safety (in the cockpit)

Perceived Organisational support

To calculate the mean scores on different dimensions of safety culture, groups of survey items were aggregated together (with a mean score being generated) according to the safety culture ‘dimension’ they

related to. This allows for analysis of the safety culture (rather than responses to a single survey item),

and for meaningful between-group comparisons to be made. Safety culture assessments often attempt to ascertain whether responses to a dimension are favourable. Although there is no definitive rule for doing

this the following interpretation is used here.

If the mean score of a dimension is under 2.5, this is considered to be of concern as it indicates most participants responded negatively to an item (thus indicating urgent action should be taken for

improvement). If a dimension mean score is between 2.5 to 3.5, this is open to interpretation as it

indicates either conflicting viewpoints, or neutrality, or uncertainty (e.g. participants indicating they ‘Neither Agree Nor Disagree’ to safety survey items). Nevertheless, from a safety standpoint,

improvement action should also be considered here, especially given the wide variations around the mean

values obtained in this survey. A dimension mean score above 3.5 is generally considered positive, as it indicates most participants responded positively to a survey item. At this level, opportunities for

improvement may still be sought, especially where they would support other more negatively rated

dimensions,

The list in Box 1 and Figure 10 below reports the mean scores for the eleven dimensions included in the

survey. It can be seen that the majority of dimension mean scores are above 3.5, indicating an overall

positive response from across the sample. Using this approach, the safety culture dimensions can be ranked as follows from positive (green) to neutral/uncertain (blue) to negative (red). Given the varying




standard deviations (i.e. variations of respondents’ ratings) around the mean values used below, this

merely presents a useful snapshot overview on where things appear satisfactory, where action may be needed, and where there is room for improvement:

Box 1 Safety Culture Dimension Mean Scores

1. Colleague commitment to safety (4.06)

2. Speaking up (3.85)

3. Risk Handling (3.77)

4. Procedures & Training (3.73)

5. Just culture and Reporting (3.71)

6. Communication and Learning (3.71)

7. Collaboration and Involvement (3.60)

8. Management commitment to safety (3.44)

9. Staff and equipment (3.44)

10. Fatigue (2.82)

11. Perceived Organisational Support (2.65)

Figure 10 Spider graph of dimension scale mean scores

1.001.502.002.503.003.504.004.505.00

Managementcommitment to safety

Collaboration andInvolvement

Just Culture andReporting

Communication andLearning

Colleague commitmentto safety

Risk HandlingProcedures & Training

Staff and equipment

Fatigue

Speaking up

PerceivedOrganisational Support




Safety Culture differences between types of organisation

To examine whether pilot responses to the safety culture dimensions were related to the type of

organisation worked for or contract type, a number of comparisons were made. There were significant differences (p<.001) between pilots working in different types of organisations for ten of the safety

culture dimensions. The common pattern was for safety culture amongst pilots at Low Cost and Cargo

airlines to be lower than those at other organisations (e.g. network airlines), see Figure 11.

For example, the following statistically significant differences were found: Cargo companies (mean=2.96)

reported significantly lower Management Commitment scores than almost all other company types

(General Aviation (mean=3.57), Business/VIP/State (mean=3.59), Charter/Leisure (mean=3.54), Low cost (mean=3.23), Network (mean=3.56) at the .001 level of significance. In addition, Low cost reported

significantly lower Management Commitment scores than Network and Charter/Leisure.

Figure 11 Means for Dimensions by Company type

00.5

11.5

22.5

33.5

44.5

5

ManagementCommitment

to Safety

Collaboration& Involvement

Just Culture &Reporting

Communication & Learning

Risk Handling

ColleagueCommitment

Staff &Equipment

Procedures &Training

Fatigue

Speaking up

PerceivedOrganisational

Support

Network

Low cost

Charter/leisure

Cargo

Aerialwork/ambulance/surveillance

Helicopter

General Aviation

Business/VIP/State




In terms of contract type, there were significant differences (p<.001) between those on different

contracts for all but two (Management Commitment to Safety and Procedures and Training) safety culture dimensions. The tendency was for pilots with atypical contracts (e.g. zero hours) to view safety culture

less positively than those on typical contracts (i.e. permanent contracts), (see Figure 12). For example,

pilots on a permanent contract had significantly more positive perceptions of fatigue (mean=2.86) in comparison to those on atypical (mean=2.49) contracts.2

Figure 12 Means for Dimensions by Contract type

2 There is a large difference between the number of pilots on typical (n=6394) and atypical (n=805) contracts.

00.5

11.5

22.5

33.5

44.5

ManagementCommitment to

Safety

Collaboration &Involvement

Just Culture &Reporting

Communication& Learning

Risk Handling

ColleagueCommitment

Staff &Equipment


Fatigue

Speaking up

PerceivedOrganisational

Support

Typicalcontract

Atypicalcontract




Comparisons of safety culture between companies3

To further examine the variations in safety culture amongst pilots, we explored whether pilots working at

different companies had diverging perceptions of safety culture. It was found that for some safety culture dimensions, scores across companies were relatively similar, and positive. However for others, scores

were divergent and heterogeneous. Four dimensions are illustrated below. Please note, companies are

anonymised, and company numbers do not map onto a single company. To support interpretation, the two lines on the graph indicate where means are either <=2.5 or >= 3.5.

The figure below reports on Colleague Commitment to Safety, which was positive for most companies. It

can be seen that the most positive company mean is 4.48 and the lowest company mean at 3.39. Overall, 94% of companies had a mean score above 3.5.

Figure 13 Means for Colleague Commitment to Safety by company (for companies with =>30 respondents)

3 At the outset of this survey it was decided not to identify individual airline companies, as these were not directly sampled, and thus response rates cannot be ascertained.




The figure below reports on Just Culture and Reporting, which varies for respondents from different

companies. It can be seen that 81% of company mean scores were above 3.5, and the range was 2.81 to 4.24.

Figure 14 Means for Just Culture and Reporting by company (for companies with =>30 respondents)

The figure below reports on Staff and Equipment, which varies for respondents from different companies.

The most positive mean is 4.26 and the lowest 2.72. Overall, 50% of companies had a mean score above 3.5.

Figure 15 Means for Staff & Equipment by company ID (for companies with =>30 respondents)




The figure below reports Perceived Organisational Support, which is quite low for most respondents from

different companies . Forty percent of company mean scores were below 2.5, and the range was 1.88 to 3.80.

Figure 16 Means for Perceived Organisational Support by company ID (for companies with =>30 respondents)

The table below reports on the proportion of companies, by safety culture dimension, with mean scores

of 2.5 or lower, between 2.5 and 3.5, and 3.5 or above.

Table 1 Proportion of company mean scores by dimension (for companies with =>30 respondents)

Safety Culture Dimension % of companies with

a mean score of

<=2.5

% of companies

with a mean

score of >2.5 to

<3.5

% of companies

with a mean

score of >=3.5

Management commitment to

safety

3 50 47

Collaboration and Involvement 0 38 62

Just Culture and Reporting 0 19 81

Communication and Learning 0 25 75

Risk Handling 0 16 84

Colleague commitment to safety 0 6 94

Staff and equipment 0 50 50

Procedures & Training 0 9 91

Fatigue 25 69 6

Speaking up 0 22 78

Perceived Organisational Support 41 53 6




Comparisons with Air Traffic Management

The figure below reports on comparisons of safety culture mean scores between air traffic controllers and

pilots. It utilised previously published data using the EUROCONTROL safety culture survey, with over 5000 controllers, from 17 countries, for six dimensions common to the survey with European pilots (Reader,

Noort et al. 2015). As can be seen below, the data from pilots is broadly equivalent to ATM.

Figure 17 Comparisons between pilots and air traffic controllers

Managementcommitment to

safety

Collaborationand

Involvement

Just Cultureand Reporting

Communication and Learning

Colleaguecommitment to

safety


ATM 3.48 3.37 3.14 3.22 3.99 3.31

Airlines 3.44 3.60 3.71 3.71 4.06 3.73

1.00

2.00

3.00

4.00

5.00

Mea

n




Discussion

According to the UK Civil Aviation Authority, a positive safety culture is the foundation of an effective

safety management system (CAA 2015). In this study, we measured perceptions of safety culture amongst 7,239 pilots working in Europe. This is equivalent to approximately 14% of the population, and one of the

largest ever safety culture studies of pilots working in commercial aviation.

This survey has a sufficient number of responses to enable an overview of safety culture amongst European pilots from across the different nations in Europe and different companies and types of airline.

The one area that is missing from this survey is the follow-up workshops used in other industries (e.g. Air

Traffic Management) as part of the full safety culture process, which enable deeper analysis and diagnosis of the reasons underlying the responses. Nevertheless, this is the first time such a pan-European survey

has been attempted, and the results paint a coherent picture of the strengths and weaknesses of safety

culture amongst pilots in Europe.

The independent authors of this report also consider the results to not be skewed towards a particular

group or viewpoint. A wide and diverse sample of pilots completed the survey. There are no extremes,

and when averaged, the results are generally positive. This survey has not been used therefore as a ‘grievance’ survey, and the responses are well-balanced, and represent the views of a substantial sample

of pilots working in European aviation.

How is European pilot safety culture, overall?

On balance, perceptions of safety culture amongst pilots working in Europe were favourable. For the

majority of items (59%) responses to the survey were above 3.5 (indicating mostly positive perceptions).

For 41% of items, scores were below 3.5, indicating mixed or negative perceptions. Furthermore, in terms of safety culture dimensions, the mean scores of 7 dimensions were above 3.5. Four dimensions were

between 2.5 and 3.5. This indicates that whilst safety culture is generally perceived positively by pilots,

attention is required, and action in several key areas is warranted.

Where is safety culture strong, and where is there room for improvement?

In terms of safety culture dimensions, pilots tend to have concerns over the issues of fatigue

management, management commitment to safety, staff and equipment, and perceived organisational support. At an individual survey item level, concerns focussed on trust in management with regard to

safety, receiving feedback on safety issues, training, national aviation authorities, and pilots being tired at

work. More positively, the vast majority of pilots felt their colleagues were committed to safety, that voicing concerns on safety was encouraged, and that they do not need to take risks that make them feel

uncomfortable about safety.

Two areas stand out from the others, namely perceived organisational support and fatigue. This latter dimension refers to the workforce feeling tired and to how fatigue is managed by the company, and

human factors research has systematically shown how fatigue has the potential to impact upon

operational safety in many industries. Perceived organisational support is a relative newcomer to safety




culture, as researchers have indicated links between this and safety practices (Reader, Mearns et al.

2016). The implication is that where a workforce feels unsupported and unsatisfied with their organization, they feel the organization is not committed to safety, does not recognise the pressures they

face, and does not value their contributions to safety. This was particularly the case for pilots on atypical

contracts, of whom 39% were aged 30 or under.

Analysis revealed the extent to which pilots who had positive or negative perceptions of safety culture

was related to the type of company they worked for (e.g. Cargo, Low Cost, Network Carrier), and their

contract with that company (e.g. typical or atypical). In general, those at Low Cost and Cargo companies, and on atypical contracts tended to view safety culture least positively. It is important to recognise that

the large majority of pilots who responded to the survey were on typical contracts (88.47%). Nonetheless,

it is a finding that needs to be considered carefully in light of the fact that more of these types of contracts and business models may be used in the future as competition increases.

The findings additionally showed considerable variation for certain safety culture dimensions between

pilots working at different companies. This indicates that safety practices at aviation companies differ, leading to differential beliefs on issues such as the extent to which management is committed to safety,

as well as resourcing issues (staffing and equipment). However, because this survey comprises varying

samples by company (e.g. we cannot ascertain response rates by company, or verify responses), data relating to individual companies must be interpreted with caution. Lastly, for the dimensions where safety

culture was comparable between ATM and pilots, safety culture amongst pilots was generally similar.

What are the next steps?

The industry and its constituents, from the airlines to the regulators, as well as the European Commission,

need to consider the results in this report. Overall the news is positive, but there are significant concerns that should be considered. Four ways forward are suggested:

1. One is to convene a series of workshops with pilots, managers and decision makers, to discuss the

results and what is beneath them, i.e. what is driving these results, and what could be changed that would bolster safety culture yet still enable European aviation to remain competitive. Such

workshops would need representation from Low Cost and Cargo airlines, as well as companies

and staff utilising atypical contracts.

2. The results of the survey indicate that pilots across the industry are concerned with fatigue

management. Over half did not believe their company takes fatigue seriously. This needs to be

addressed by actions undertaken jointly with regulators, airlines and representative bodies, to educate managers and pilots about the potential safety implications and also the necessity to

improve this cultural dimension.

3. Given the different perception of safety culture according to the type of contracts under which pilots work, the regulatory authorities should consider how to take this factor into account to




ensure the continued safety of operations. The results from this survey raise questions about the

potential impact on safety culture of atypical contracts.

4. On a more strategic level, commercial aviation, as is done in other safety critical industries (e.g.

ATM, Oil and Gas), needs to begin systematically measuring and exploring safety culture in commercial aviation companies. The data indicates quite wide variations in perceptions of safety

culture according to company, and this might be explored further. For example, within the Future

Sky Safety programme of work, several airlines are already embarking on specific safety culture studies. This approach allows the management of such companies, as well as other staff besides

pilots, to have their say. If this is achieved, learning on safety culture (e.g. sharing best practices

amongst organisations) can begin to occur across European airlines as it already occurs for Air Traffic organisations.

Conclusions

This is the first major independent survey of the safety culture of European pilots, achieving a return rate

of more than 7000 pilots. The results show that pilot perceptions of safety culture are generally positive.

However, the survey also reveals significant differences in assessment of safety culture depending on factors such as the type of airlines pilots work for, or the type of contract they work to. Pilots working on

atypical contracts and those working for low cost and cargo airlines have more negative perceptions of

safety culture than their colleagues working under more secure forms of employment and for network carrier airlines. Perceptions of management commitment to safety, staffing and equipment, fatigue and

perceived organisational support were not especially positive across the whole sample.

Aviation has the reputation of being the safest mode of transport, and indeed other modes of transport (rail, road and sea) look to the industry to learn how to do safety better. This survey represents a

significant learning opportunity for the aviation industry, to reflect on why it is safe, and also where it

needs to address certain issues to ensure that it continues to remain safe in the future.




MAIN REPORT




1 INTRODUCTION

1.1. The context

The aviation industry in Europe been transformed over recent decades. A combination of global economic

changes, changing customer demands, and increases in airlines with alternate business models (Jorens, Gillis et al. 2015) has made the industry incredibly competitive. In addition, the nature of regulation has

changed, with both national and European-wide bodies having a role in industry governance.

Nonetheless, European aviation remains an ultra-safe industry. The European Aviation Safety Agency (EASA) report that in European Commercial Aviation, an average of 1.3 accidents (with 64.2 fatalities) has

occurred per year since 2005(EASA 2016). To put this into context, there can be approximately 30,000

flights in European Airspace on a typical summer day, and over 800 million passengers travel per year in the European Union alone. Overall, there are few than 0.5 fatal accidents per million flight departures in

Europe, In terms of non-fatal accidents, there have been on average 24 non-fatal accidents and 75.8

serious incidents per year since 2005(EASA 2016). These figures have remained relatively stable, and compare favourably to the rest of the world. This highly impressive safety record can be explained by

many factors, for example: technology and airframes, automation, standardisation, safety protocols,

regulation, air crew training, working directives, the external environment and the traditionally strong commitment to safety from aviation professionals. Arguably most important has been an industry-wide

culture of safety, which has led to and sustained the above efforts to minimise and avoid threats to

safety. Indeed, due to the low frequency of accidents and near-misses, and the non-linear relationship between profitability and safety (Madsen 2011), safety culture has become a key indicator for assessing

safety practices and susceptibility to safety problems within aviation organisations.

Yet, within the European aviation industry, there is currently no systematic method or practice of measuring and comparing safety culture amongst pilots. The current report applies a psychometrically

established tool for measuring safety culture in the aviation industry (in air traffic management) to a

sample of pilots working in Europe.

1.2. Safety culture: definition and background

Safety culture is a sub-facet of organisational culture (Reason 1997, Clarke 1999, Cooper 2000). It is made up of safety-related norms (or basic assumptions), values, and practices shared by groups (Guldenmund

2000). Simply, it comprises of how people feel (psychological aspects), what they do (behavioural aspects)

and how the organisation operates (situational aspects) in relation to safety (Cooper 2000). The concept rose to prominence after the Chernobyl nuclear disaster where it became apparent that the organisation's

poor safety culture contributed to the preventable tragedy (International Atomic Energy Agency 1986).

Discussions on safety culture often refer to the topic of safety climate, with the terms being used interchangeably. This reflects a long-standing, if not terribly useful, debate on the differences between

the two (Zohar 1980). Most commonly, safety climate is considered to be a temporary snapshot of the




current safety culture made up of perceptions and feelings (likened to mood), while safety culture is more

stable (and compared to personality) and relevant to group activities and organisational histories (Cox and Flin 1998). Safety climate focuses on managerial prioritisation of safety (Zohar 2010), and culture the

safety-related values and practices that more widely permeate the organisation (Reader, Noort et al.

2015). In this study, we focus on the topics covered by safety climate (management commitment to safety), and also a range of enduring practices that are reflect of safety culture (e.g. incident reporting

practices, relationships, cooperation with colleagues). Thus, our focus is on safety culture, with the

concepts measured within safety climate being subsumed within this theoretical framework.

Safety culture research is common across most high-risk industries. For example, construction (Chinda and

Mohamed 2008), offshore environments (Cox and Cheyne 2000), healthcare (Halligan and Zecevic 2011),

nuclear power (Lee and Harrison 2000), aviation (O’Connor, O’Dea et al. 2011), air traffic management (Mearns, Kirwan et al. 2013), shipping (Havold 2005), and rail (Clarke 1998). Many methods exist to

measure safety culture (e.g. interviews, focus groups, observations), however surveys are most often used

(Huber 1991, Reason 1997, Conchie, Donald et al. 2006). Surveys typically involve organisational members responding to questionnaire items that relate to a number of ‘latent dimensions’: for example the

commitment of management to safety, incident reporting practices, fatigue, the support given by an

organisation (e.g., resources) to improve safety, communication on safety (Reader, Noort et al. 2015).

Where responses to such dimensions are assessed as shared and positive across an organisation, safety

culture is conceptualized as ‘strong’, and to be a positive indicator of safety. Conversely, negative,

opposite or fragmented perceptions tend to indicate a ‘weak’ safety culture, where responders view safety-related values and practices within the organisation (e.g. on attitudes and behaviours for working

when sick or fatigued) as problematic.

Research shows that organisations with a poor safety culture are more prone to accidents, while those with a strong safety culture are more resilient (Clarke 2006). However, this finding has not been

demonstrated in the aviation industry, primarily due to very low rate of incident occurrence (e.g.

compared to healthcare). Nonetheless, safety culture measurement has become widely used method to gather insight on (e.g. strengths, weaknesses, areas for improvement) the safety practices of employees

and managers and organisational safety management strategies.

Safety culture in the aviation industry

Safety culture is a concept deeply embedded within the aviation industry (e.g. airlines, manufacturers, air

traffic control). This is due to the recognition that threats to safety will always exist, and that where they manifest they have the potential to be catastrophic (Gill and Shergill 2004). In particular, safety culture

issues have been established as a major causal factor in aviation accidents (Aarons 2011) , and as a

consequence organisations have developed advanced safety management systems. These are “a proactive and integrated approach to managing safety including the necessary organisational structures,

accountabilities, policies and procedures” (CAA 2015). Safety management systems comprise of safety

policy and objectives, safety risk management, safety assurance, and safety promotion: they are most




effective when “built on a foundation of a positive safety culture” (CAA, 2015, p4). Thus, various tools for

measuring safety culture exist across the aviation industry: in Air Traffic Control (Mearns, Kirwan et al. 2013), aircraft maintenance (McDonald, Corrigan et al. 2000, Kim and Song 2016), ground handling (Ek

and Akselsson 2007), and for cabin crews (Kao, Stewart et al. 2009). Indeed, due to the high standards

established for managing safety in the aviation industry, it is has become a model upon which safety management strategies are emulated in other sectors (Kapur, Parand et al. 2016).

In terms of safety culture amongst pilots, relatively few academic studies have focussed on this cohort. A

review of 23 studies has shown that most safety culture studies have pertained to military flight crews, and only three on commercial pilots (O’Connor, O’Dea et al. 2011). For example, Evans et al (2007)

examined safety climate in Australia. Their survey focussed on the dimensions of ‘Management

commitment to safety’, ‘Safety training’, and ‘Equipment and maintenance’ (Evans, Glendon et al. 2007). A survey of 904 pilots found no significant differences between pilots from different company types (e.g.

charter, aerial and public transport pilots), and suggested that this was due to the strong professional

culture amongst pilots superseding organisational culture (Evans, Glendon et al. 2007), although pilot-specific response patterns were not reported. Research by Gibbons (2006) tested a five-factor model

(focussing upon organisational commitment, management involvement, pilot empowerment, reporting

systems, and accountability systems) safety culture amongst 503 pilots in a large US airline. Again, pilot response patterns were not reported. Also developing a safety culture metric, Gill and Shergil found that,

amongst 172 pilots in New Zealand, ‘pilots’ perceive luck and safety to be the most important factor in

aviation safety. However, pilot specific patterns were not reported

A more recent study of an Asia-Pacific Airline with a sample of 417 pilots found the overall safety culture

of the airline to be ‘healthy’, with respondents providing positive feedback in issues such as the safety

reporting system and company philosophy (Gao, Bruce et al. 2013). More junior staff and those with shorter tenure in the airline were more positive about safety culture, perhaps due to having been less

exposed to safety problems. Research using the safety attitudes questionnaire has shown, amongst 163

crews working, that perceptions of safety culture within a single airline can vary considerably (e.g. on management commitment to safety), and that these relate to behaviours in the cockpit (Sexton, Klinect et

al. 2001).

In terms of other parts of the aviation industry, a small set research has focussed upon engineers and maintenance crews. For example, showing maintenance engineers to highly value the implementation of

safety policies and procedures (in comparison to other staff groups) (Gill et al., 2004), the paradoxical

pressures on safety and economic interests experienced by aircraft maintenance staff (Atak and Kingma 2011), that aircraft technicians can have a relatively homogeneous professional sub-culture spanning

different organisations (McDonald, Corrigan et al. 2000), and that ground handling staff tend to have

quite positive perceptions of safety culture, although less so than estimated by managers (Ek and Akselsson 2007). In Europe, research with pilots has shown that pilots are increasingly working to new and

less stable employment contracts, with the implications for safety being unclear 4.

4Jorens, Y., Gillis, D., Valcke, L., & De Coninck, J. ‘Atypical Forms of Employment in the Aviation S ector’, European




Arguably, in comparison to other domains of aviation, the amount of safety culture research that has

been conducted with pilots is quite modest. For example, the air traffic management industry (ATM). This is one of the safest components of civil aviation industry, with Air Navigation Service Providers (ANSPs)

operating in a single interconnected industry to manage air traffic. ATM performance is based upon

having a safe and reliable system, as when mishaps occur (e.g. the Überlingen mid-air collision in 2002) they can be catastrophic. Thus, a strong safety culture (e.g. for incident reporting, learning from near-

events, resource management, safety communication, collaboration) is a crucial part of safety

management in the ATM industry.

To this end, EUROCONTROL (European Organisation for the safety of air navigation) has instituted a pan-

European approach to safety culture measurement in ATM. In partnership with the University of

Aberdeen (2006-2011) and the London School of Economics (2012-present), a psychometrically tested measurement tool has been developed for measuring safety culture in European ATM. The survey tool is

part of a wide toolkit (e.g. focus groups, observations) that is used to measure safety culture in European

ANSPs (e.g. with controllers, engineers, managers). These data are used to monitor for potential problems in an ANSP’s safety culture (e.g. comparing data to industry norms), to identify strengths and

opportunities for improvement, and to evaluate the impact of organisational change (e.g. over time).

To date, over 25 ANSPs have participated in the programme (with some being surveyed multiple times), with data being gathered from over 20,000 respondents. The programme has received very positive

recognition from the ATM sector (as evidence by changes in industry practices and conferences on safety

culture) and scientific community, and is currently one the largest safety culture programmes in the world. In terms of academic safety culture research, the work has shown that i) safety culture can be

reliably measured across different countries, ii) ANSPs vary considerably in their safety culture, with

factors such as national environments explaining this, iii) management and controllers can develop quite divergent beliefs around safety culture in an ANSP, and iv) safety culture can be meaningfully

benchmarked and used to stimulate inter-organisational learning across the industry in Europe.

Yet, at present there is no such programme within any other part of the aviation industry. In particular, there has been relatively little focus on pilots, which is surprising given the inspiration the airline industry

has given to other domains in terms of safety management (Kapur, Parand et al. 2016). This study applies

the safety culture survey methodology used in ATM to pilots working in the European airline industry.

Social Dialogue, European Commission, 2015.




1.3. Pilot’ perceptions of safety culture in the European Aviation industry: the current study

Research within the airline industry indicates the lack of i) a systematic and widespread approach to measuring perceptions of safety culture amongst pilots in the civil aviation industry, ii) a previously

validated model for measuring safety culture amongst pilots working internationally, iii) norm data for

how individual pilots view safety culture, iv) norm data safety culture in different airlines, and v) a methodology for learning and using safety culture data to improve safety management systems.

To begin this process with pilots, we applied and adapted the well-established safety culture

measurement tool used in European ATM to pilots working European civilian aviation. This was to facilitate i) evaluations of pilot observations on organisational safety culture within the European aviation

industry, ii) identification of areas where the industry is strong and has opportunity for improvement, iii)

comparisons between the experiences of pilots in different sectors, organisations, and personal contexts, iv) the assessment of upward or downward trends in safety culture, v) evaluations between airline pilots

and other parts of the industry (e.g. ATM) in order to gather a more holistic picture of safety culture in

European aviation, and vi) the establishment of associations between organisational safety culture data and actual safety data.

The current study is the first European-wide safety culture survey of pilots working in the civil aviation

industry. It is funded by the European Commission as part of the ‘Future Sky Safety’ initiative, and was supported by the European Cockpit Association (the representative body of European pilots at European

Union (EU) level).

1.4. Objectives

The study aim is to explore perceptions of European pilots on their company safety culture and factors

that may affect these perceptions. Specifically, the report intends to:

1. Apply a safety culture measurement tool used in the ATM industry to pilots working in European civil aviation

2. Profile, at the questionnaire-item and dimension level, broad safety culture trends amongst

pilots in the European aviation industry 3. Inspect whether there are variations in safety culture according to the characteristics of

pilots (e.g. type of company worked for, contract type)

4. Examine whether there are variations in safety culture amongst the companies at which pilots report working

5. Reflect on safety culture data collected from pilots in relation to data collected in Air Traffic

Management




2 METHODS

2.1. Safety culture measurement

The study utilised the EUROCONTROL safety culture survey, which has been used extensively and psychometrically validated in European Air Traffic Management. The questionnaire is part of a larger

toolkit that is used to measure, understand, and improve safety culture in ATM. The purpose is to

measure staff (e.g. operational, management, engineers) assessments and beliefs on safety culture within their Air Navigation Service Provider (ANSP). The survey items underlying the tool were developed

through a literature review and qualitative investigation (interviews, focus groups, incident analyses).

Data from the survey is used to structure workshops and interviews on safety culture (e.g. to understand specific safety problems), and a prototype version of the questionnaire was tested in four ANSPs in 2008.

A larger investigation, with 17 ANSPs and data from nearly 6500 participants was used to establish a

measurement model for assessing safety culture across Europe.

For the current study, we adapted the EUROCONTROL safety culture survey to ensure it was relevant for

commercial pilots working in European Aviation (Mearns, Kirwan et al. 2013). The process, with the support of the European Cockpit Association, involved consulting a steering group of senior pilots working

within a number of airlines. The questionnaire was amended through a series of iterations (e.g. adapting

items relating to work in ATM to pilots), with each question being reviewed, amended where appropriate, and tested with a small sample of respondents. In order to address pilot-specific issues, some additional

questions were added to the survey. This involved an entirely new demographics section relevant for

pilots (e.g. whether they were a pilot or co-pilot), items on fatigue, speaking up and perceived-organisational support, and two additional independent items ('When I am unwell, I do not go into work.'

and ‘My national aviation authority takes safety seriously’). The focus on this emerged from the

(recognised within the industry) importance of fatigue as a factor impacting upon the safe operations of pilots, and the importance of organisations creating an environment where pilots feel supported and are

able to raise personal and performance related issues. In addition, item phrasing was amended for the

survey audience (e.g. “people in the organisation” to “pilots in this company”).

The final survey comprised a total of 58 items covering eight safety culture dimensions: collaboration &

involvement; just culture & reporting; communication & learning; risk handling; colleague commitment to safety; staff & equipment; procedures & training; and management commitment to safety. A three-item

fatigue management scale, a two-item speaking up scale and a validated eight-item perceived

organisational support scale (Eisenberger, Hungtington et al. 1986), along with 14 demographic questions. These are: nationality; country based in; gender; age; company name; company type; contract type; job

title; management role; tenure; training background; flying experience; and aircraft type. In addition,

there were 3 independent items (e.g. ‘Safety is taken seriously in this company’).




The questionnaire was predominantly split by general questions about safety culture (Section B in the

questionnaire), more specific questions linked to operational safety (Section C) and by questions on the working life of pilots more generally and how much they feel supported by their organisation (Section D).

The full set of study items are reported in the table below.

Table 2 Questionnaire items & dimensions

DEMOGRAPHICS

What country are you based in? What is your nationality? What is your gender? What is your age? What company do you mainly fly for? What type of company do you work for? What type of contract do you have? Do you work part-time or part-year in your current company? (If PT) What percentage of time do you work, on average? What is your job title? Do you have a management role? How long have you been working in your company? What is your flying experience? Please indicate where you first learned to fly as a professional pilot? What aircraft type do you currently fly?

MANAGEMENT COMMITMENT TO SAFETY

My direct manager is committed to safety. My direct manager takes action on the safety issues we raise. My direct manager would always support me if I had a concern about safety. Pilots have a high degree of trust in management with regard to safety.

COLLABORATION & INVOLVEMENT

Maintenance are able to promptly repair technical deficiencies to the aircraft. Good communication exists between Flight Operations and Engineering/Maintenance to ensure safety. My involvement in safety activities is sufficient. There are people who I do not want to work with because of their negative attitude to safety. (R) Pilots who raise safety issues are seen as troublemakers. (R) Other people in this company understand how my job contributes to safety.

JUST CULTURE & REPORTING

Pilots who report safety-related occurrences are treated in a just and fair manner. Voicing concerns about safety is encouraged. We get timely feedback on the safety issues we raise. I am satisfied with the level of confidentiality of the reporting and investigation process. I am prepared to speak to my direct manager when unsafe situations are developing. A staff member who regularly takes unacceptable risks would be disciplined or corrected in this

company.

COMMUNICATION & LEARNING

Information about safety-related changes within this company is clearly communicated to staff. We learn lessons from safety related incident or occurrence investigations. I have good access to information regarding safety incidents or occurrences within the company. There is good communication up and down the company about safety.




I read reports of incidents or occurrences that are relevant to our work. People in this company share safety related information.

RISK HANDLING

Changes to the company, systems and procedures are properly assessed for safety risk. We often have to deviate from procedures. (R) I have to take risks that make me feel uncomfortable about safety. (R)

COLLEAGUE COMMITMENT TO SAFETY

My colleagues are committed to safety. I have confidence in the people that I interact with in my normal working situation. Everyone I work with in this company feels that safety is their personal responsibility.

STAFF & EQUIPMENT

We have sufficient staff to do our work safely. We have the equipment needed to do our work safely. We have sufficient practical support from our safety manager/department.

PROCEDURES & TRAINING

I have sufficient opportunity to regularly practice my manual flying skills. I feel entirely comfortable to fly my aircraft. Adequate training is provided when new systems and procedures are introduced. I have sufficient training to understand the procedures associated with my work. We have procedures that are politically or legally focused rather than safety or practical focused. The SOPs associated with my work are appropriate to ensure safe operations

INDEPENDENT ITEMS

Safety is taken seriously in this company. When I am unwell, I do not go to work. My national aviation authority takes safety seriously.

FATIGUE

Pilots in this company are often tired at work. (R) I would feel comfortable to complete a fatigue report. The issue of fatigue is taken seriously by this company.

SPEAKING-UP IN THE COCKPIT

First officers are willing to challenge Captains on their decision making Captains encourage their crew to speak-up if they are concerned with decisions made

PERCEIVED ORGANISATIONAL SUPPORT

The organization values my contribution to its well-being. The organization fails to appreciate any extra effort from me. (R) The organization would ignore any complaint from me. (R) The organization really cares about my well-being. Even if I did the best job possible, the organization would fail to notice. (R) The organization cares about my general satisfaction at work. The organization shows very little concern for my well-being. (R) The organization takes pride in my accomplishments at work.

PSYCHOLOGICAL CONTRACT

I feel this company reciprocates the effort put in by its pilots

(R)=Reverse (negatively) worded item




2.2. Data collection

The survey was electronic, and managed through the ‘Qualtrics’ survey platform. It was distributed via an

online link between January 18th and March 8th 2016. In total, the European Cockpit Association represents 38,000 pilots in 37 states (and is an umbrella organisation for national associations), and the

aim of the study was to reach as many of these pilots as possible. Active pilots working in a range of

industries (e.g. passenger, cargo, helicopter) were targeted. The European Cockpit Association promoted the survey to their member associations through newsletters and on social media. Twitter and targeted

face-book adverts presented the survey to wider audiences.

2.3. Study participants

There were a total of 7,239 valid responses included in the study and subsequent analyses. This is after

removal of surveys that did not meet a number of criteria for detecting non-meaningful or fraudulent entries (e.g. partial completion, completion time, lack of sensitivity to negatively worded items, and a

number of other criteria). Within these 7,239 responses there were still missing responses (e.g. to a single

item). These are responses missing completely at random. We handled these missing variables using pairwise deletion. This means that we identify that these responses are missing and we remove them

from the case, but include all other responses from the respondent with the missing data. Similarly for

tests of difference (ANOVAs) we excluded cases ‘analysis by analysis’.

2.4. Demographic analysis

To profile our sample, the demographic data was analysed in a number of ways. First, text responses were recoded into categories. For example, company names which were entered manually were anonymised

into letters (e.g. Company A, Company B). Answers written in the ‘Other’ response category (e.g. for

training background) were either recoded into existing categories (e.g. military) or a new category (e.g. National flight school - state funded). Second, we then computed the total number of responses of each

group. This involved calculating the raw number of respondents within each group, and the proportion of

the sample they covered. Third, demographic groups were cross-tabulated. In particular, age and contract type, company type and contract type, company type and tenure, company type and flying experience,

contract type and flying experience, age and training background, and company type and training

background.

2.5. Descriptive analysis of survey items

Using the software package SPSS, we checked the normal distribution of survey items. We then ran descriptive statistics comprising frequencies, means, ranges and standard deviations (SD) for

all items in the survey. Please see

Table 3 for an explanation of these terms.




Table 3 Statistical definitions




Calculating safety culture dimensions

To generate overall dimension scores, the scores of each item that related to a dimension was added up and divided by the number of items in that dimension to create a mean score and standard deviation. We

then checked inter-item reliability with Cronbach’s alpha to see whether responses to the items under the

dimension heading are consistent with one another (indicating they are measuring the same construct). Please see Table 2 for questionnaire items grouped by dimensions, and Table 17 for dimension inter-item

reliability scores.

We did not include the item ‘good communication exists between pilots and air traffic control to ensure

safety’ under the Communication & Learning dimension because this item may be more indicative of

problems outside of the airline. Similarly, we did not include the item ‘I feel fully supported by my company if I report unfit to fly” in the Perceived Organisational Support scale, as it was an additional item

generated for this survey only. The individual results for these items can be found in the descriptive data.

The survey dimensions are included in Table 2. For each dimension, the overall mean score was calculated. Group comparisons were then made.

2.6. Group comparisons

We used T Tests and One-Way Analysis of Variance (ANOVAs) to check statistically for significant

differences on each safety culture dimension between the following groups: The type of company worked

for; job role (Captain, First Officer, Second Officer); Contract type; Managerial responsibilities; Flying experience; Gender; Age; Country base; Nationality; Company.

Where there were more than two groups, we used ANOVAs. Otherwise T Tests were used. If we were

testing one independent variable at a time, we used a One-Way ANOVA. If two independent variables were tested together, we used a Two-Way ANOVA. In this report, we only focus on significant differences

between groups, and these are illustrated with Spider Diagrams.

Due to the large and unequal sample size of different groups, the variances of the response patterns by different groups were examined in order to assess which comparative statistic was most appropriate for

comparing the respondent groups. To do this, we checked the homogeneity of variance using a Levene’s

test, and the following strategy was applied. If the Levene’s test was not significant, thereby indicating equal variances, we proceeded with interpretation of the ANOVA table with post-hoc Scheffé tests

(Scheffé is used when there are mostly samples of unequal sizes). If the Levene’s test was significant,

indicating unequal variances, we used Welch and Brown-Forsyth tests, which are more conservative tests of difference and used Games-Howell to examine post-hoc comparisons. This approach has been

recommended by expert statisticians (Field 2013)




An additional check where equal variance assumptions were violated was also undertaken. This involved

running the non-parametric test, Kruskall-Wallis, to compare results. Where there was a non-significant result in the non-parametric test, we report this finding.

Finally, we use a stringent significance level of p>0.001. This reduces the chances of Type 1 errors, i.e. the

likelihood of rejecting the null hypothesis when it is true. This reduces the likelihood of finding significant differences.

For country, nationality and company ID, we applied a threshold cut-off point of >=30 respondents per

group. This allowed for inclusion in all statistical tests (i.e. ANOVAs will not present output tables if there are groups with a value of 1) and for the results to representative by group.

For all ANOVAs, the assumptions of normality were not satisfied for the dependent dimension variables

tested, with skew results all greater than 1 and a Shapiro-Wilk test presenting a significant p value of p<.000. However, the sample is large enough that parametric tests are appropriate and ANOVAs are not

very sensitive to moderate deviations from normality; studies with non-normal distributions found the

false positive rate is not affected very much (Glass et al. 1972).

In order to test how meaningful the significant differences between two groups are, we calculated the

effect sizes for ANOVAs and T-tests using Cohen’s d, which considers effect sizes of 0.2 to be small, 0.5 to

be medium and 0.8 to be large (Cohen 1992).

Correlations between dimensions are performed through Pearson’s tests and for ordinal demographic

groups through Spearman’s Rho Tests. Only the significant differences are described.

2.7. Comparing responses from participants in different airlines

Finally, we examined the response patterns from survey respondents working in different commercial

airlines. Where more than 30 respondents reported working for a single airline, we aggregated those responses together to generate an airline score, and compared scores. This data is anonymised (i.e. we

do not report any airline name within the report), and must be caveated. Specifically, our survey did not

sample any airlines directly, meaning that any data collected from pilots working in a given airline is not necessarily reflective of the organisation as a whole (i.e. many pilots will not have responded to the

survey). In addition, we cannot ascertain for definite whether pilots do work for the airlines they report

working for. Rather, our interest is in whether responses from pilots in some airlines differ significantly from those in others – i.e. to what extent is the ‘safety cultures’ perceived by respondents working in

different airlines homogenous or heterogeneous? Homogeneity would indicate, broadly, pilots working in

commercial European aviation to have a ‘shared’ safety culture, regardless of where they work. Heterogeneity would indicate pilot beliefs about safety culture are driven by practices specific to airlines,

which vary from the perspective of pilots.




3 RESULTS

3.1. Responses

We received a total of 7,239 valid responses (14% population response rate).

3.2. Demographics

The table below presents the sample demographics (missing responses not included). It can be seen that

the vast majority of respondents report working for a European company (whether airline, or other

organisation). For 34 organisations, there were 30 or more respondents reported working for the same organisation. For nine organisations, over 200 respondents reported working for the same organisation. In

total, 3962 respondents reported working for a 'network' airline (flag/legacy carriers who have a big

network of international destinations and provide a range of pre-flight and onboard services, including different service classes, and connecting flights)(Reitchmuth 2008), and 1708 for a 'low cost' airline (no

frills service focused on cost reduction and delivering lowest fares)(Reitchmuth 2008).

Table 4: Company Demographics

COMPANY DEMOGRAPHICS n %

Sample: Report European company 6667 92.14

Report worldwide company 71 0.98

Do not report company 501 6.88

Total 7239 100.00

Company: 1-10 respondents 189 71.86

11-30 respondents 40 15.21

31-50 respondent 7 2.66






501+ Respondents 2 0.76

Total 263 100.00

Company type: Aerial work/ambulance/surveillance 51 0.71

Business 129 1.79

Cargo 435 6.03

Charter/leisure 543 7.53

General Aviation 135 1.87

Helicopter 108 1.50

Low cost 1708 23.67

Network 3962 54.91

Other (Please state) 144 2.00

Total 7215 100.00




The figure below graphically shows the respondents by company, with nearly 2000 responses from pilots

reporting to work for three airlines.

Figure 18 Respondents per company (for companies with =>30 respondents)

The figure 19 graphically shows the respondents by company type. It can be seen that over 85% of the

sample reported working for passenger airlines (low cost, network, charter/leisure), and further 6% for

cargo airlines.

758708

453425

379347

319226

184148

140139

120118

112106105

9084

79787470

63504946

3835333030

0 100 200 300 400 500 600 700 800

AGAFAEADACABAA

ZYXVUTSRQPONM

LKJI

HGFEDCBA

Number of respondents

Com

pany

ID




Figure 19 Company type

The table below reports the countries from which pilots are based. It can be seen that the majority of

pilots (64%) report being based in Germany, France, Spain, UK, Netherlands, and Switzerland. Six countries (Azerbaijan, Belarus, Bosnia and Herzegovina, FYR Macedonia, Georgia and Slovenia) had only

one respondent.

Table 5 Pilots’ country base

Country Based n % Country Based n % Country Based n %

Albania 4 0.06 FYR Macedonia 1 0.01 Poland 27 0.37

Austria 123 1.71 Georgia 1 0.01 Portugal 172 2.39

Azerbaijan 1 0.01 Germany 1597 22.15 Romania 26 0.36

Belarus 1 0.01 Greece 18 0.25 Russia 4 0.06

Belgium 124 1.72 Hungary 12 0.17 Serbia 3 0.04 Bosnia & Herzegovina 1 0.01

Iceland 80 1.11 Slovak Republic 4 0.06

Bulgaria 4 0.06 Ireland 230 3.19 Slovenia 1 0.01

Croatia 52 0.72 Italy 243 3.37 Spain 527 7.31

Cyprus 6 0.08 Latvia 10 0.14 Sweden 394 5.46

Czech Republic 5 0.07 Lithuania 10 0.14 Switzerland 538 7.46

Denmark 233 3.23 Luxembourg 222 3.08 Turkey 24 0.33

Estonia 3 0.04 Malta 19 0.26 Ukraine 2 0.03

Finland 137 1.90 Netherlands 609 8.45 United Kingdom 789 10.94

France 556 7.71 Norway 297 4.12 Other 101 1.40

Total: 7211 100.00

2% 6%

7%

2%

24%55%

2% Aerialwork/ambulance/surveillance

Business

Cargo

Charter/leisure

General Aviation

Helicopter

Low cost

Network

Other (Please state)




2% 2% 3%2%

8%

23%

1%3%

4%3%9%

4%

3%

8%

6%

8%

11%

Austria

Belgium

Denmark

Finland

France

Germany

Iceland

Ireland

Italy

Luxembourg

Netherlands

Norway

Portugal

Spain

Sweden

Switzerland

United Kingdom

The figure below graphically demonstrates the countries from which pilots are based, excluding those

countries which covered less than 1% of respondents (i.e. 70 pilots). Germany had the most pilots (23%), and Iceland the least (1.1%).

Figure 20 Country base (This figure does not include countries that make up less than 1 % of the sample)




Table 6 reports on the nationality of respondents. Nearly 60% of respondents were from the Netherlands,

France, Germany, Sweden, and the UK.




3% 3%4%

12%

2%

9%

23%1%4%

3%

4%

2%

5%

8%

6%

11%

Austrians

Belgians

Danes

Dutch

Finns

French citizens

Germans

Icelanders

Irish

Italians

Norwegians

Portuguese

Spaniards

Swedes

Swiss

United Kingdom (British)

Table 6 Nationality of respondents (excludes nationalities that make up less than 1% of the sample)

Nationality n % Austrians 176 2.45 Belgians 204 2.84 Danes 263 3.66 Dutch 800 11.14 Finns 126 1.76 French citizens 607 8.46 Germans 1570 21.87 Icelanders 91 1.27 Irish 243 3.38 Italians 209 2.91 Norwegians 272 3.79 Portuguese 158 2.20 Spaniards 368 5.13 Swedes 539 7.51 Swiss 438 6.10 British) 770 10.73

Total 6834 95.19

The figure below graphically illustrates the nationality of respondents, excluding those countries which covered only 1% of respondents (i.e. 7 pilots). The most represented nationality was German (23%), and

Iceland the least (1.27%). The majority were from Northern and Western European countries.

Figure 21 Nationality of respondents (excludes countries that make up less than 1 % of the sample)




The table below reports on the following demographic characteristics: gender, age, job, contract type,

managerial role, tenure in company, flying experience, and training.

Table 7 Pilot Demographics

PILOT DEMOGRAPHICS

n % Gender: Male 6889 95.73

Female 307 4.27 Total 7196 100.00 Age: 18-30 1082 14.99 31-40 2158 29.89 41-50 2331 32.29 51-60 1419 19.66 60+0 229 3.17 Total 7219 100.00 Job: Captain 4037 56.09 First Officer 3089 42.91 Second Officer 72 1.00 Total 7198 100.00 Contract type: Typical contract 6394 88.47

(Permanent contract) 6394 88.47 Atypical contract 805 11.14 (Self-employed contract 317 4.39 Zero-hours contract 209 2.89 Fixed-term contract

P 257 3.56

Pay-to-fly contract) 22 0.30 Other 28 0.39 (Unemployed/retired

Ot 13 0.18

Other) 15 0.21 Total 7227 100.00 Management role: Yes (flight operations & training) 694 9.64

Yes (safety department) 119 1.65 Yes (other including union/company council) 47 0.65 No 6339 88.05 Total 7199 100.00 Tenure in company: <1yr 319 4.42 1-4yrs 1371 18.98 5-10yrs 2030 28.10 11yrs+ 3504 48.50 Total 7224 100.00 Flying experience: <1000 202 2.79 1000-3000 745 10.31 3001-5000 1007 13.93 5001-10000 2092 28.94 10000+ 3183 44.03 Total 7229 100.00 Training: Airline funded cadetship 1693 23.69 Military 795 11.12 National flight school - state funded 296 4.14 Self-funded cadetship, with an airline (integrated)

training 1215 17.00

Self-funded, modular training 3032 42.42 Self-funded, self-improver (non-modular) 22 0.31 University - State funded 42 0.59 Other 52 0.73 Total 7147 100.00




The figure below shows that approximately 96% (n=6889) of pilots were male.

Figure 22 Gender

The figure below shows that the data was split almost in half between First Officers (43%) and Captains (56%), and only 1% of responses came from Second Officers. This is representative of the industry, as

there are slightly more Captains, and very few Second Officers presently working in European airlines.

Figure 23 Job Title

96%

4%

MaleFemale

Captain56%

First Officer43%

Second Officer

1%




The figure below reports on the age of pilots participating in the survey. The age group 41-50 was the

most represented (32%), and 60+ the least represented (3%).

Figure 24 Age

The figure below reports on the flying experience of pilots participating in the survey. Over 40% of pilots

had greater than 10,000 flight hours. Thirteen percent had completed less than 3000 hours.

Figure 25 Flying experience

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

18-30

31-40

41-50

51-60

60+0

2.79

10.31

13.93

28.94

44.03

0.00 10.00 20.00 30.00 40.00 50.00

<1000

1000-3000

3001-5000

5001-10000

10000+

%

%




The figure below reports on the proportion of pilots in a managerial role. Most (88%) were not in a

management role, whilst nearly 10% had a management role for flight operations and training.

Figure 26 Management role

The figure below reports on the tenure of pilots in their company. Nearly half (48.5%) had been in their

company for 11 years or more. Under 5% had been in their company for less than a year.

Figure 27 Tenure in company

9.64

1.65

0.65

88.05

0.00 20.00 40.00 60.00 80.00 100.00

Yes (flight operations & training)

Yes (safety department)

Yes (other includingunion/compny council)

No

4.42

18.98

28.10

48.50

0.00 10.00 20.00 30.00 40.00 50.00 60.00

<1yr

1-4yrs

5-10yrs

11yrs+

%

%




24%

11%

4%

17%

42%

Airline funded cadetship

Military

National flight school - statefundedSelf-funded cadetship, with anairline (integrated) trainingSelf-funded, modular training

Self-funded, self improver(non-modular)University - State funded

Other

88.47%

11.14%

Typical contract

Atypicalcontract

Other

The figure below reports on contract type. It shows that that the vast majority of pilots (88.47%) had a

typical contract, whilst a minority (11.14%) of pilots were on an atypical contract.

Figure 28 Contract type

Typical contract = permanent contract; Atypical contract = Self-employed, Zero hours, Fixed-term, and Pay-to-Fly contracts.

The figure below reports on training background of pilots. Most pilots (42%) had been self-funded, whilst a further 24% had been supported by an airline.

Figure 29 Training background

Please see Appendices 1 for further demographic group cross-tabulations.




3.3. Reporting item-by-item

This section reports the descriptive statistics by item for the whole sample, split by sections of the

questionnaire. Overall there are high Standard Deviations (SDs) indicating substantial variations between pilots. For the total sample, this is expected because the pilots come from diverse backgrounds and

contexts (e.g. different geographical locations, airlines and training backgrounds).

3.3.1. Q Section B – Descriptive statistics of all respondents by items in section B of survey

Table 8 reports on the mean scores for all items, by all respondents, in section B (General) of the safety

culture survey. It can be seen that for all items the full range of response options (1-5) were used. The

overall mean score for all section B items was 3.66, and the standard deviation was .994. Safety culture researchers tend to utilise the score ‘3.5’ as an ad-hoc indicator of whether a safety culture is positive or

problematic. This indicates that, across the entire sample, responses to section B of the survey were

generally positive. Additionally, the Standard Deviation shows that there is a lot of variation in these opinions.

Table 8 Survey Section B descriptive data

Range Min Max Mean SD

B01 My colleagues are committed to safety. 4 1 5 4.43 .725

B02 Voicing concerns about safety is encouraged. 4 1 5 4.00 .929

B03 We have sufficient staff to do our work safely. 4 1 5 3.27 1.127 B04 Everyone I work with in this company feels that safety is their personal responsibility.

4 1 5 3.73 0.948

B05 My direct manager is committed to safety. 4 1 5 3.79 1.016

B06 Pilots have a high degree of trust in management with regard to safety. 4 1 5 2.95 1.182 B07 I have confidence in the people that I interact with in my normal working situation.

4 1 5 4.01 .798

B08 Pilots who report safety-related occurrences are treated in a just and fair manner.

4 1 5 3.84 1.047

B09 People in this company share safety-related information. 4 1 5 3.79 .988

B10 My direct manager takes action on the safety issues we raise. 4 1 5 3.50 .992 B11 Information about safety-related changes within this company is clearly communicated to staff.

4 1 5 3.64 1.009

B12 We get timely feedback on the safety issues we raise. 4 1 5 3.23 1.060

B13 My involvement in safety activities is sufficient. 4 1 5 3.70 0.823

B14r Pilots who raise safety issues are seen as troublemakers. 4 1 5 3.70 1.120 B15 I am prepared to speak to my direct manager when unsafe situations are developing.

4 1 5 3.96 0.911

B16 There is good communication up and down the company about safety. 4 1 5 3.30 1.077 B17 Changes to the company, systems and procedures are properly assessed for safety risk.

4 1 5 3.23 1.061

B18 Safety is taken seriously in this company. 4 1 5 3.80 1.017 B19 We learn lessons from safety-related incident or occurrence investigations.

4 1 5 3.93 .938

B20 My direct manager would always support me if I had a concern about safety.

4 1 5 3.53 1.039

B21 We have sufficient practical support from our safety manager/department.

4 1 5 3.42 0.998

B22 I have good access to information regarding safety incidents or occurrences within the company.

4 1 5 3.43 1.131

B23r There are people who I do not want to work with because of their negative (e.g. loose, careless) attitude to safety.

4 1 5 3.56 1.150




B24 Other people in this company understand how my job contributes to safety.

4 1 5 3.57 0.929

B25 When I am unwell, I do not go to work. 4 1 5 3.85 1.068 B26 If I see unsafe behaviour by any of my colleagues I would talk to them about it.

4 1 5 4.06 .748

The table below reports on the extent to which pilots gave a ‘favourable’ or ‘unfavourable’ response to

each survey item in Section B. Items are highlighted where over 25% of respondents responded unfavourably. The most and least favourable responses are reported on the following page.

Table 9 Survey Section B Favourable and Unfavourable responses

%

Unfavourable %

Neither %

Favourable

B01 My colleagues are committed to safety. 2.46 4.05 93.49

B02 Voicing concerns about safety is encouraged. 8.29 12.62 79.09

B03 We have sufficient staff to do our work safely. 27.77 21.77 50.46

B04 Everyone I work with in this company feels that safety is their personal responsibility.

12.43 19.48 68.09

B05 My direct manager is committed to safety. 11.88 17.99 70.13

B06 Pilots have a high degree of trust in management with regard to safety.

38.08 24.98 36.94

B07 I have confidence in the people that I interact with in my normal working situation.

5.58 11.74 82.68


12.13 16.78 71.09

B09 People in this company share safety-related information. 12.38 15.11 72.51

B10 My direct manager takes action on the safety issues we raise. 15.56 27.67 56.77

B11 Information about safety-related changes within this company is clearly communicated to staff.

15.13 19.76 65.11

B12 We get timely feedback on the safety issues we raise. 24.87 29.77 45.36

B13 My involvement in safety activities is sufficient. 8.44 24.24 67.33

B14r Pilots who raise safety issues are seen as troublemakers. 17.24 18.26 64.50

B15 I am prepared to speak to my direct manager when unsafe situations are developing.

8.39 12.52 79.08

B16 There is good communication up and down the company about safety.

23.80 25.39 50.81

B17 Changes to the company, systems and procedures are properly assessed for safety risk.

25.36 28.58 46.07

B18 Safety is taken seriously in this company. 11.73 18.74 69.53

B19 We learn lessons from safety-related incident or occurrence investigations.

9.15 12.98 77.87


15.32 28.57 56.11


18.47 27.40 54.13


22.48 20.10 57.42


21.82 16.57 61.60


13.95 24.08 61.97

B25 When I am unwell, I do not go to work. 14.14 13.44 72.42

B26 If I see unsafe behaviour by any of my colleagues I would talk to them about it.

4.04 11.31 84.65




0% 20% 40% 60% 80% 100%

B01 My colleagues are committed tosafety.

B26 If I see unsafe behaviour by any of mycolleagues I would talk to them about it.

B07 I have confidence in the people that Iinteract with in my normal working

situation.

B02 Voicing concerns about safety isencouraged.

B15 I am prepared to speak to my directmanager when unsafe situations are

developing.

Unfavourable

Neither

Favourable

The figure below reports on the five section B items pilots responded to most favourably (i.e. agreed with

a positive statement on safety culture, and disagreed with a negative statement). For the item B01 “My colleagues are committee to safety”, 93% of pilots responded favourably to this item. This was followed

by the item B26 “If I see unsafe behaviour by any of my colleagues I would talk to them about it” (84%).

This indicates pilots to feel positively about the safety practices of their colleagues.

Figure 30 Top 5 most favourable responses in section B




0% 20% 40% 60% 80% 100%

B06 Pilots have a high degree of trust inmanagement with regard to safety.

B03 We have sufficient staff to do ourwork safely.

B17 Changes to the company, systems andprocedures are properly assessed for

safety risk.

B12 We get timely feedback on the safetyissues we raise.

B16 There is good communication up anddown the company about safety.

Unfavourable

Neither

Favourable

The figure below reports on the five section B items pilots responded to least favourably (i.e. disagreed

with a positive statement on safety culture, and agreed with a negative statement). For the item B06 “Pilots have a high degree of trust in management with regard to safety”, only 37% of pilots gave a

favourable response. For the item B03, only 50% of pilots responded favourably to “We have sufficient

staff to do our work safely”. This indicates some overall concerns over management commitment to safety and resourcing.

Figure 31 Top 5 least favourable responses overall in section B




3.3.2. Q Section C – Descriptive statistics of all respondents by items in section C

The table below reports on the mean scores for all items, by all respondents, in section C of the safety

culture survey (operational). It can be seen that for all items the full range of response options (1-5) were used. The overall mean score for all section C items was 3.77, and the standard deviation was .94. Safety

culture researchers tend to utilise the score ‘3.5’ as an ad-hoc indicator of whether a safety culture is

positive or problematic. This indicates that, across the entire sample, responses to section C of the survey were generally positive. The Standard Deviation shows a high degree of variation in these opinions.

Table 10 Survey Section C descriptive data

Range Min Max Mean SD C01 We have the resources needed to do our work safely. 4 1 5 3.62 .965 C02 I read reports of incidents or occurrences that are relevant to our work.

4 1 5 4.15 .758

C03 We have procedures that are focused on appearing to follow the rules, rather than improving practice.

4 1 5 3.42 1.025

C04 Good communication exists between pilots and Engineering/Maintenance to ensure safety.

4 1 5 3.63 .964

C05 I am satisfied with the level of confidentiality of the reporting and investigation process.

4 1 5 3.54 1.117

C06r We often have to deviate from procedures for safety reasons. 4 1 5 3.99 .824 C07 I have sufficient opportunity to regularly practice my manual flying skills.

4 1 5 3.59 1.186

C08 Maintenance are able to promptly repair technical deficiencies to the aircraft.

4 1 5 3.44 1.067

C09 Adequate training is provided when new systems and procedures are introduced.

4 1 5 2.98 1.140

C10r I have to take risks that make me feel uncomfortable about safety.

4 1 5 4.10 .920

C11 Good communication exists between pilots and Air Traffic Control to ensure safety.

4 1 5 3.87 0.865

C12 A staff member who takes unacceptable risks would be disciplined or corrected in this company.

4 1 5 3.68 0.963

C13 I feel entirely confident to fly my aircraft. 4 1 5 4.34 .714 C14 The SOPs associated with my work are appropriate to ensure safe operations.

4 1 5 4.00 0.815

C15 Good communication exists between flight crew and cabin crew to ensure safety.

4 1 5 3.96 0.865

C16 I have sufficient training to understand the procedures associated with my work.

4 1 5 4.04 0.824




The table below reports on the extent to which pilots gave a ‘favourable’ or ‘unfavourable’ response to

each survey item in Section C. The most and least favourable responses are reported on the following pages.

Table 11 Survey Section C Favourable and Unfavourable responses

%

Unfavourable %

Neither %

Favourable

C01 We have the resources needed to do our work safely. 15.38 18.03 66.59 C02 I read reports of incidents or occurrences that are relevant to our work.

3.95 7.60 88.45


20.04 28.55 51.41


13.76 21.96 64.28


19.58 19.48 60.95

C06r We often have to deviate from procedures for safety reasons.

5.55 15.17 79.29

C07 I have sufficient opportunity to regularly practice my manual flying skills.

21.27 14.37 64.37


21.58 20.93 57.48


36.03 25.28 38.69


7.39 11.59 81.02


7.69 16.47 75.84


12.67 19.53 67.80

C13 I feel entirely confident to fly my aircraft. 2.38 6.15 91.47 C14 The SOPs associated with my work are appropriate to ensure safe operations.

5.95 11.74 82.31


6.66 15.06 78.28


6.01 11.05 82.94




0% 20% 40% 60% 80% 100%

C13 I feel entirely confident to fly myaircraft.

C02 I read reports of incidents oroccurrences that are relevant to our

work.

C16 I have sufficient training tounderstand the procedures associated

with my work.

C14 The SOPs associated with my workare appropriate to ensure safe

operations.

C10r I have to take risks that make mefeel uncomfortable about safety.

Unfavourable

Neither

Favourable

The figure below reports on the five section C items pilots responded to most favourably (i.e. agreed with

a positive statement on safety culture, and disagreed with a negative statement). For the item C13 “I feel entirely confident to fly my aircraft”, 91% of pilots responded favourably to this item. This was followed

by the item C02 “I read reports of incidents or occurrences that are relevant to our work” (85%). Pilots

also reported (83%) feeling “I have sufficient training to understand the procedures associated with my work” (C16). This indicates a general feeling of positivity amongst pilots towards their skills and

knowledge for ensuring safe operations.

Figure 32 Top 5 most favourable responses in Section C

The figure below reports on the five section C items pilots responded to least favourably (i.e. disagreed with a positive statement on safety culture, and agreed with a negative statement). For the item C09

“Adequate training is provided when new systems and procedures are introduced”, 38% of pilots gave a

favourable response. For the item C08, 21% of pilots responded unfavourably to “Maintenance are able to promptly repair technical deficiencies to the aircraft”. This indicates some concern over the systems for

ensuring safe operations.




Figure 33 Top 5 least favourable responses in Section C

3.3.3. Q Section D – Descriptive statistics of all respondents by items in section D

The following tables report on the mean scores for all items, by all respondents, in section D of the safety culture survey (working life). It can be seen that for all items the full range of response options (1-5) were

used. The overall mean score for all section D items was 2.927, and the standard deviation was 1.06.

Safety culture researchers tend to utilise the score ‘3.5’ as an ad-hoc indicator of whether a safety culture is positive or problematic. This indicates that, across the entire sample, responses to section D of the

survey were generally not positive.

The table below reports on the items focussing on perceived organisational support. It shows that, in

general, pilots feel their organisations do not care adequately for their well-being or value them. The

Standard Deviation shows a high degree of variation in these opinions.

Table 12 Survey Section Descriptives: Perceived Organisational Support (n=6893)

Range Min Max Mean SD D03r The company shows very little concern for my well-being. 4 1 5 2.70 1.183 D05 The company takes pride in my accomplishments at work. 4 1 5 2.64 1.056 D09 The company values my contribution to its well-being. 4 1 5 2.71 1.094 D11 The company really cares about my wellbeing. 4 1 5 2.36 1.097 D13r The company fails to appreciate any extra effort from me. 4 1 5 2.56 1.135 D14 The company cares about my general satisfaction at work. 4 1 5 2.40 1.065 D15r Even if I did the best job possible, the company would fail to notice.

4 1 5 2.53 1.135

D16r The company would ignore any complaint from me. 4 1 5 3.36 1.018

0% 20% 40% 60% 80% 100%

C09 Adequate training is providedwhen new systems and procedures are

introduced.

C08 Maintenance are able to promptlyrepair technical deficiencies to the

aircraft.

C07 I have sufficient opportunity toregularly practice my manual flying

skills.

C03 We have procedures that arefocused on appearing to follow the

rules, rather than improving practice.

C05 I am satisfied with the level ofconfidentiality of the reporting and

investigation process.

Unfavourable

Neither

Favourable




The table below reports on the items focussing on fatigue. It shows that, in general, pilots feel fatigued

and that often their organisation does not support them on this issue. The Standard Deviation shows a high degree of variation in these opinions.

Table 13 Survey Section D Descriptives: Fatigue (n=6896)

Range Min Max Mean SD D01r Pilots in this company are often tired at work. 4 1 5 2.42 1.089 D06 I would feel comfortable to complete a fatigue report. 4 1 5 3.48 1.190 D12 The issue of fatigue is taken seriously by this company. 4 1 5 2.57 1.118 D17 I feel fully supported by my company if I report unfit to fly. 4 1 5 3.08 1.177

The table below reports on the items focussing on speaking -up. It shows that, in general, pilots feel

positively on this issue.

Table 14 Survey Section D Descriptives: Speaking-up (n=6872)

Range Min Max Mean SD D02 First officers are willing to challenge Captains on their decision making.

4 1 5 3.74 .846

D08 Captains encourage their crew to speak-up if they are concerned with decisions made by the Captain.

4 1 5 3.96 0.789

The table below reports on the items focussing on their national aviation authority's approach to safety. Overall, perceptions of pilots were not especially positive.

Table 15 Survey Section D Descriptives: National Authority (n=6841)

Range Min Max Mean SD D04 My national aviation authority manages safety reports well. 4 1 5 2.88 .933 D07 My national aviation authority takes safety seriously. 4 1 5 3.25 1.053

The table below reports on the extent to which pilots gave a ‘favourable’ or ‘unfavourable’ response to each survey item in Section D. Please note, item D10 was not included in the survey due to a numbering

error. The most and least favourable responses are reported on the following page.




Table 16 Survey Section D Favourable and Unfavourable responses

%

Unfavourable %

Neither %

Favourable D01r Pilots in this company are often tired at work. 57.78 22.73 19.90 D02 First officers are willing to challenge Captains on their decision making. 10.33 16.72 72.94 D03r The company shows very little concern for my well-being. 44.49 26.83 28.64 D04 My national aviation authority manages safety reports well. 28.33 46.36 23.62 D05 The company takes pride in my accomplishments at work. 43.58 34.48 21.46 D06 I would feel comfortable to complete a fatigue report. 23.93 14.43 61.72 D07 My national aviation authority takes safety seriously. 22.48 31.07 45.81 D08 Captains encourage their crew to speak-up if they are concerned with decisions made by the Captain. 5.19 14.82 79.82 D09 The company values my contribution to its well-being. 41.69 31.90 26.04 D11 The company really cares about my wellbeing. 57.52 27.16 17.27 D12 The issue of fatigue is taken seriously by this company. 50.05 26.83 23.06 D13r The company fails to appreciate any extra effort from me. 53.30 24.75 22.44 D14 The company cares about my general satisfaction at work. 55.26 27.56 17.24 D15r Even if I did the best job possible, the company would fail to notice. 53.57 25.16 21.77 D16r The company would ignore any complaint from me. 20.02 29.47 50.70 D17 I feel fully supported by my company if I report unfit to fly. 31.73 25.70 42.41




0% 20% 40% 60% 80% 100%

D08 Captains encourage their crewto speak-up if they are concerned

with decisions made by the Captain.

D02 First officers are willing tochallenge Captains on their decision

making.

D06 I would feel comfortable tocomplete a fatigue report.

D16r The company would ignoreany complaint from me.

D07 My national aviation authoritytakes safety seriously.

Unfavourable

Neither

Favourable

The figure below reports on the five section D items pilots responded to most favourably (i.e. agreed with

a positive statement on safety culture, and disagreed with a negative statement). For the item D08 “Captains encourage their crew to speak-up if they are concerned with decisions made by the Captain”,

80% of pilots responded favourably to this item.

Figure 34 Top 5 most favourable responses in section D




0% 20% 40% 60% 80% 100%

D01r Pilots in this company are oftentired at work.

D11 The company really cares aboutmy wellbeing.

D14 The company cares about mygeneral satisfaction at work.

D15r Even if I did the best jobpossible, the company would fail to

notice.

D13r The company fails toappreciate any extra effort from me.

Unfavourable

Neither

Favourable

The figure below reports on the five section C items pilots responded to least favourably (i.e. disagreed

with a positive statement on safety culture, and agreed with a negative statement). For the item D09 “Pilots in this company are often tired at work”, 58% of pilots gave an unfavourable response.

Figure 35 Top 5 least favourable responses in section D




3.4. Safety culture dimensions

In this section, we focus on the latent dimensions measured by the safety culture questionnaire items. To

recap, groups of individual survey items refer to broader conceptual themes (e.g. Management Commitment to Safety), and we utilise these ‘dimensions’ to interpret the results of the survey, and to

make group comparisons. Please see the methods (section 2.6) for details on the dimensions are

calculated, the items underlying the themes, and the dimensions themselves.

3.4.1. Dimension Descriptive Statistics & Reliability

Groups of survey items were aggregated together (with a mean score being generated) according to the safety culture ‘dimension’ they relate to (e.g. management commitment to safety). This allows for analysis

of the safety culture (rather than responses to a single survey item), and for meaningful between group

comparisons to be made. Safety culture assessments often attempt to ascertain whether responses to a dimension are positive or not. Although there is no definitive rule for doing this the following

interpretation is often used.

If the mean score of a dimension is under 2.5, this is considered concerning as it indicates most participants responded negatively to an item (thus indicating opportunities for improvement). If a

dimension mean score is between 2.5 to 3.5, this is somewhat open to interpretation as it indicates either

conflicting viewpoints, or uncertainty (e.g. participants indicating they ‘Neither Agree Nor Disagree’ to safety survey items). The implications of this depend on the topic under investigation. A dimension mean

score above is 3.5 generally considered positive, as it indicates most participants responded positively to a

survey item.

The figure below reports the mean scores for the 11 dimensions included in the survey. It can be seen that

the majority of dimension mean scores are above 3.5, indicating a positive response from across the

sample. This includes: Colleague commitment to safety (4.06); Speaking up (m=3.85); Risk Handling (3.77); Procedures & Training (m=3.73); Just culture and Reporting (3.71); Communication and Learning

(m=3.71); Collaboration and Involvement (m=3.60). However, pilots indicated uncertainty on the

following: Management commitment to safety (m=3.44); Staff and equipment (m=3.44); Fatigue (m=2.82); Perceived Organisational Support (m=2.65).




Figure 36 Spider graph of dimension scale mean scores

The table below reports descriptive data on the survey scales. It can be seen that for two scales, staff and equipment and procedures and training, the scores were less than optimal (alpha >0.6). This means that

all items underlying these dimensions may not be measuring the exact same concept.

Table 17 Dimension scale descriptive statistics and reliability

Dimension (items) N (valid)

N (missing)

Range Min Max Mean SD alpha

Management commitment to safety (B05;B06;B10;B20)

7163 76 4.00 1.00 5.00 3.44 .90 .876

Collaboration and Involvement (B13;B14R;B23R;B24;C04;C08)

6868 371 4.00 1.00 5.00 3.60 .65 .719

Just Culture and Reporting (B02;B08;B12;B15;C05;C12)

6855 384 4.00 1.00 5.00 3.71 .72 .806

Communication and Learning (B09;B11;B16;B19;B22;C02)

6859 380 4.00 1.00 5.00 3.71 .77 .866

Colleague commitment to safety (B01;B04; B07)

7213 26 4.00 1.00 5.00 4.06 .65 .686

Risk Handling (B17;C06;C10) 6900 339 4.00 1.00 5.00 3.77 .70 .607 Procedures & Training

(C03;C07;C09;C13;C14;C16) 6848 391 4.00 1.00 5.00 3.73 .53 .523

Staff and equipment (B03;B21;C01) 6892 347 4.00 1.00 5.00 3.44 .87 .795 Fatigue (D01R;D06;D12) 6864 375 4.00 1.00 5.00 2.82 .89 .686 Speaking up (D02;D08) 6847 392 4.00 1.00 5.00 3.85 .67 .500

Perceived Organisational Support (D03R;D05;D09;D11;D13R;D14;D15R;D16R)

6758 481 4.00 1.00 5.00 2.65 .88 .921

1.001.502.002.503.003.504.004.505.00

Managementcommitment to safety

Collaboration andInvolvement

Just Culture andReporting

Communication andLearning

Colleague commitmentto safety

Risk HandlingProcedures & Training

Staff and equipment

Fatigue

Speaking up

Perceived OrganisationalSupport

Mean




3.4.2. Dimension correlations

Pearson’s correlations show significant correlations between all the dimensions at the =>.001 significance

level. This is expected as these are all dimensions of safety culture, and significant associations are more likely in a large sample.

Table 18 Dimension correlations

Management

Commitment to Safety

Collaboration &

Involvement

Just Culture & Reporting

Communication &

Learning

Risk Handling

Colleague Commitmen

t

Staff & Equipment

Procedures & Training Fatigue Speaking up

Perceived Organisation

al Support


Pearson Correlation 1 .700** .800** .733** .640** .609** .749** .495** .621** .311** .678**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 7163 6809 6801 6797 6835 7139 6830 6781 6798 6779 6698


Pearson Correlation .700** 1 .748** .725** .672** .648** .705** .553** .606** .409** .620**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6809 6868 6792 6794 6828 6848 6822 6773 6789 6771 6693


Pearson Correlation .800** .748** 1 .798** .649** .646** .729** .498** .622** .404** .626**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6801 6792 6855 6778 6817 6833 6810 6768 6774 6758 6683


Pearson Correlation .733** .725** .798** 1 .627** .624** .752** .513** .604** .375** .618**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6797 6794 6778 6859 6818 6838 6814 6765 6779 6760 6678

Risk Handling Pearson Correlation

.640** .672** .649** .627** 1 .530** .643** .513** .525** .298** .525**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6835 6828 6817 6818 6900 6879 6850 6805 6821 6800 6717

Colleague Commitment

Pearson Correlation

.609** .648** .646** .624** .530** 1 .595** .432** .464** .410** .456**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 7139 6848 6833 6838 6879 7213 6871 6825 6841 6825 6736

Staff & Equipment

Pearson Correlation .749** .705** .729** .752** .643** .595** 1 .538** .655** .296** .661**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6830 6822 6810 6814 6850 6871 6892 6798 6813 6793 6707


Pearson Correlation

.495** .553** .498** .513** .513** .432** .538** 1 .435** .287** .440**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6781 6773 6768 6765 6805 6825 6798 6848 6771 6758 6677

Fatigue Pearson Correlation

.621** .606** .622** .604** .525** .464** .655** .435** 1 .275** .740**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6798 6789 6774 6779 6821 6841 6813 6771 6864 6813 6736

Speaking up Pearson Correlation

.311** .409** .404** .375** .298** .410** .296** .287** .275** 1 .261**

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6779 6771 6758 6760 6800 6825 6793 6758 6813 6847 6711

Perceived Organisational Support

Pearson Correlation

.678** .620** .626** .618** .525** .456** .661** .440** .740** .261** 1

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 N 6698 6693 6683 6678 6717 6736 6707 6677 6736 6711 6758

**. Correlation is significant at the 0.001 level (2-tailed).




3.4.3. Between group differences

Between group differences for company type, contract type, Job title, part-time/year & full-time and

gender are reported through ANOVAs and T Tests. Only the significant differences are described and illustrated with Spider Diagrams.

The assumptions of normality were not satisfied for the dependent variables tested, with skew results all

greater than 1 and a Shapiro-Wilk test presenting a significant p value of p<.000. However, the sample is large enough that parametric tests are appropriate.

We have presented effect sizes to show how where we have stronger (higher) or weaker (lower)

differences between the means. A low score indicates that the differences are significantly different, but not necessarily meaningfully different.

The ANOVA summary tables show any significant differences between groups by dimension, and post hoc

tests reveal where (i.e. between which groups) the significant differences exist.

Please see the Appendices for the safety culture dimension mean scores by demographic group.

3.4.3.1. Company type

Summary overview

The figure below plots all of the mean scores (and error bars) for each safety culture dimension according to the type of company pilots report working for.




Figure 37 Means and Error bars for all dimensions by Company type

Overall, the data indicates that pilots at Cargo and Low cost companies had more negative views of safety

culture, with those at Network airlines holding the most positive views.




The table below reports the mean scores for each safety culture dimension according to the type of

company pilots report working for.

Table 19 Mean scores by company type

Company type

Network Low cost Charter/leisur

e Cargo

Aerial work/ambulance

/surveillance Helicopter General Aviation

Business/VIP/State Other


3.56 3.23 3.54 2.96 3.64 3.38 3.57 3.59 4.00

Collaboration & Involvement 3.70 3.41 3.62 3.42 3.66 3.48 3.50 3.57 3.17

Just Culture & Reporting 3.84 3.50 3.76 3.32 3.61 3.46 3.48 3.71 4.00

Communication & Learning 3.88 3.37 3.78 3.41 3.66 3.68 3.48 3.64 4.00

Risk Handling 3.83 3.68 3.78 3.65 3.65 3.47 3.47 3.70 2.67

Colleague Commitment 4.16 3.89 4.06 3.89 3.89 3.88 3.88 3.90 4.00

Staff Equipment 3.60 3.11 3.47 3.10 3.57 3.38 3.28 3.54 4.00

Procedures & Training 3.74 3.68 3.77 3.74 3.75 3.72 3.69 3.83 3.50

Fatigue 2.99 2.38 2.95 2.48 3.55 3.09 3.24 3.21

Speaking up 3.91 3.79 3.79 3.80 3.57 3.64 3.40 3.77 3.00


2.78 2.25 2.93 2.38 3.39 2.89 3.05 3.18 3.18




Analysis on the variations of mean scores showed that Levene’s Tests of Homogeneity of Variance were

violated for all dimensions (i.e. the dimensions had unequal variances), apart from Speaking up and POS.

ANOVA and Welch and Brown-Forsyth tests all showed that there were significant differences among all

dimensions apart from Procedures & Training. The table below shows the ANOVA results.

Table 20 ANOVA overview of significant differences between groups for company type

Sum of Squares df Mean Square F Sig.

Management Commitment to Safety Between Groups 248.304 7 35.472 45.247 .000 Within Groups 5585.737 7125 .784 Total 5834.040 7132

Collaboration & Involvement Between Groups 114.320 7 16.331 39.680 .000 Within Groups 2813.149 6835 .412 Total 2927.469 6842

Just Culture & Reporting Between Groups 213.098 7 30.443 63.111 .000 Within Groups 3290.675 6822 .482 Total 3503.773 6829

Communication & Learning Between Groups 351.374 7 50.196 93.865 .000 Within Groups 3650.352 6826 .535 Total 4001.726 6833

Risk Handling Between Groups 54.104 7 7.729 15.920 .000 Within Groups 3333.999 6867 .486 Total 3388.104 6874

Colleague Commitment Between Groups 118.591 7 16.942 41.794 .000 Within Groups 2908.441 7175 .405 Total 3027.032 7182

Staff & Equipment Between Groups 340.122 7 48.589 68.706 .000 Within Groups 4850.649 6859 .707 Total 5190.771 6866

Procedures & Training Between Groups 6.082 7 .869 3.149 .003 Within Groups 1880.553 6815 .276 Total 1886.635 6822

Fatigue Between Groups 552.751 7 78.964 111.560 .000 Within Groups 4835.849 6832 .708 Total 5388.600 6839

Speaking up Between Groups 42.511 7 6.073 13.801 .000 Within Groups 2998.484 6814 .440 Total 3040.995 6821

Perceived Organisational Support Between Groups 461.067 7 65.867 92.520 .000 Within Groups 4789.801 6728 .712 Total 5250.869 6735




Management Commitment

Post-hoc Games-Howell pairwise comparisons showed that Cargo airlines reported significantly lower Management Commitment scores than almost all other company types (General Aviation,

Business/VIP/State, Charter/Leisure, Low cost, Network) at the .001 level of significance. Low cost

reported significantly lower Management Commitment scores than Network and Charter. All other comparisons were not significant.

The effect sizes for Cargo and Network (Cohen’s d = 0.684393); Cargo and Charter/Leisure (Cohen’s d =

0.658227); Cargo and Business/VIP/State (Cohen’s d = 0.667644); Cargo and General Aviation (Cohen’s d = (0.637114) were all medium to large. The effect size for Cargo and Low cost (Cohen’s d = 0.297438) was

low. Low cost and Network (Cohen’s d =0.372989); Low cost and Charter/Leisure (Cohen’s d = 0.350097),

are all considered to be between low to medium.

The mean differences for Cargo and Network (0.59744); Cargo and Charter/Leisure (0.57990); Cargo and

Business/VIP/State (-0.62870); Cargo and General Aviation (-0.60755) were all medium to large. The effect

size for Cargo and Low cost (0.26671) was low. Low cost and Network (-0.33074); Low cost and Charter/Leisure (0.31319), are all considered to be between low.

Please see Appendix 3 Table 43 for percentage differences by company type per item.

Figure 38 Means for Management Commitment to Safety by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo

Aerialwork/ambulance

/surveillanceHelicopter

General Aviation

Other (Pleasestate)

Business/VIP/State






Post-hoc Games-Howell pairwise comparisons showed that both Cargo and Low cost companies reported significantly lower Collaboration & Involvement scores than Charter/Leisure and Network at the .001 level

of significance.

The effect sizes for Cargo and network (Cohen’s d = 0.448657); Cargo and Charter/Leisure (Cohen’s d = 0.320416); Low cost and network (Cohen’s d = 0.448286); Low cost and Charter/Leisure (Cohen’s d =

0.324883), are all considered to be between low to be medium, based on statistical guidance (Cohen

1992).

The mean differences Cargo and network (0.27801); Cargo and Charter/Leisure (0.20034); Low cost and

network (0.28854); Low cost and Charter/Leisure (0.21088), are all considered to be low.


Figure 39 Means for Collaboration & Involvement by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo

Aerialwork/ambulanc…Helicopter

General Aviation

Other (Pleasestate)

Business/VIP/State





Just culture

Post-hoc Games-Howell pairwise comparisons showed that Cargo reported significantly lower Just Culture scores than Business/VIP/State, Charter/Leisure, Low cost, Network. Low cost reported

significantly lower Just Culture scores than Charter/Leisure and Network; and Helicopter reported

significantly lower Just Culture scores than Network.

The effect sizes for Cargo and Charter/Leisure (Cohen’s d = 0.605879), Cargo and Network (Cohen’s d =

0.721315) are considered to be between low to medium, while Cargo and Business/VIP/State (Cohen’s d =

0.484291), Low cost and Charter/Leisure (Cohen’s d = 0.367102), Low cost and Network (Cohen’s d = 0.483891), Helicopter and Network (Cohen’s d = 0.489924) are considered to be close to medium and

Cargo and Low cost (Cohen’s d = 0.244813) is low.

The mean difference for Cargo and Charter/Leisure (-0.44415), Cargo and Network (-0.52099) are considered to be between low to medium and medium respectively, while Cargo and Business/VIP/State (-

0.39219), Low cost and Charter/Leisure (-0.25853), Low cost and Network (-0.33537), Helicopter and

Network (0.38199) and Cargo and Low cost (-0.18562) are considered to be low.


Figure 40 Means for Just Culture by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo

Aerialwork/ambulance/surveillance

Helicopter

General Aviation

Other (Pleasestate)

Business/VIP/State






Post-hoc Games-Howell pairwise comparisons showed that both Cargo and Low cost companies reported significantly lower Communication & Learning scores than Charter/Leisure and Network at the .001 level

of significance.

The effect sizes for Cargo and Charter/Leisure (Cohen’s d = 0.523037), and Low cost and Charter/Leisure (Cohen’s d = 0.543103) are considered to be medium, and Cargo and Network (Cohen’s d = 0.66243), and

Low cost and Network (Cohen’s d =0.67202.) are medium to high.

The mean difference for Cargo and Charter/Leisure (0.37175), and Low cost and Charter/Leisure (0.41658) and Cargo and Network (-0.46761) are considered to be low to medium, and Low cost and

Network (-0.51243) is medium.


Figure 41 Means for Communication & Learning by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo


General Aviation

Other (Pleasestate)

Business/VIP/State





Risk Handling

Post-hoc Games-Howell pairwise comparisons showed that Network reported significantly higher Risk Handling (risk prioritisation and management) scores than Cargo, Low cost and Helicopter at the .001

level of significance.

The effect sizes for Network and Cargo (Cohen’s d=0.273336), and Network and Low cost (Cohen’s d= 0.22746) are low and for Network and Helicopter (Cohen’s d=0.501206) are considered to be medium.

The mean differences for Network and Cargo (0.18774) and Network and Low cost (0.15917) are low and

for Network and Helicopter (0.36694) are considered to be medium.


Figure 42 Means for Risk Handling by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo

Aerialwork/ambulan…Helicopter

General Aviation

Other (Pleasestate)

Business/VIP/State

Risk Handling





Post-hoc Games-Howell pairwise comparisons showed that Network reported significantly higher Colleague Commitment scores than Low cost, Cargo, Business/VIP/State and Helicopter. Charter/Leisure

reported significantly higher Colleague Commitment scores than Low cost and Cargo at the .001 level of

significance.

The effect sizes for Network and Low cost (Cohen’s d = 0.431989), Network and Cargo (Cohen’s d =

0.435697.), Network and Business/VIP/State (Cohen’s d = 0.379847), Network and Helicopter (Cohen’s d =

0.415645.) are considered to be between low and medium. Charter/Leisure and Low cost (Cohen’s d = 0.268583), and Charter/Leisure Cargo (Cohen’s d =0.271742) are low.

The mean difference for Network and Low cost (0.27471), Network and Cargo (0.27635), Network and

Business/VIP/State (0.25970), Network and Helicopter (0.28700), Charter/Leisure and Low cost (0.17521), and Charter/Leisure Cargo (0.17685) are all considered to be low.


Figure 43 Means for Colleague Commitment by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo


General Aviation

Other (Pleasestate)

Business/VIP/State





Staff & Equipment

Post-hoc Games-Howell pairwise comparisons showed that both Cargo and Low cost companies reported significantly lower Staff & Equipment scores than Charter/Leisure and Business/VIP/State and Network

airlines.

The effect sizes for Cargo and Charter/Leisure (Cohen’s d = 0.431261), Cargo and Business/VIP/State (Cohen’s d = 0.511988), and Cargo and Network airlines (Cohen’s d = 0.603942), and Low cost and

Charter/Leisure (Cohen’s d = 0.411263), Low cost and Business/VIP/State (Cohen’s d = 0.490101), and Low

cost and Network airlines (Cohen’s d = 0.579428) are all considered to be of medium effect size.

The mean difference for Cargo and Charter/Leisure (0.37349), Cargo and Business/VIP/State (-0.43799),

and Low cost and Charter/Leisure (0.362914), Low cost and Business/VIP/State (-0.42742) and Low cost

and Network airlines (0.49354) are all considered to be of low to medium effect size, and Cargo and Network airlines (-0.50412) is medium.


Figure 44 Means for Staff & Equipment by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo


/surveillanceHelicopter

General Aviation

Other (Pleasestate)

Business/VIP/State

Staff Equipment




Fatigue

Post-hoc Games-Howell pairwise comparisons showed that both Low cost and Cargo reported significantly lower scores on Fatigue (i.e. poorer scores) than every other company type (General Aviation,

Aerial work/ambulance/surveillance, Helicopter Business/VIP/State, Charter/Leisure, Network). Aerial

work/ambulance/surveillance reported significantly higher (more positive) scores on Fatigue than Charter and Network.

The effect sizes for Low cost and General Aviation (Cohen’s d = 0.961441.), Low cost and Aerial

work/ambulance/surveillance (Cohen’s d = 1.3937), Low cost and Helicopter (Cohen’s d = 0.716873.), Low cost and Business/VIP/State (Cohen’s d = 0.951748), Low cost and Charter/Leisure (Cohen’s d =

0.668021.), and Low cost and Network (Cohen’s d = 0.718741) are all high. Similarly, Cargo and General

Aviation (Cohen’s d = 0.900396), Cargo and Aerial work/ambulance/surveillance (Cohen’s d =1.359779), Cargo and Business/VIP/State (Cohen’s d =0.889921) are all high. Cargo and Helicopter (Cohen’s d =

0.646811), Cargo and Charter/Leisure (Cohen’s d =0.588398), and Cargo and Network (Cohen’s d

=0.642194) are all medium.

Aerial work/ambulance/surveillance and Charter (Cohen’s d = 0.735287), and Aerial

work/ambulance/surveillance and Network (Cohen’s d = 0.684848) and medium to high.

The mean difference for Low cost and General Aviation (-0.85816), Low cost and Aerial work/ambulance/surveillance (-1.16975), Low cost and Helicopter (-0.71401), Low cost and

Business/VIP/State (-0.83196), Low cost and Charter/Leisure (-0.56877), and Low cost and Network (-

0.61101) are all medium or high.

Similarly, Cargo and General Aviation (-0.76115), Cargo and Aerial work/ambulance/surveillance (-

1.07274), Cargo and Business/VIP/State (-0.73495), Cargo and Helicopter (-0.61700), Cargo and

Charter/Leisure (-0.47175), and Cargo and Network (-0.51400) are all medium or high. Aerial work/ambulance/surveillance and Charter (0.60099), and Aerial work/ambulance/surveillance and

Network (0.55874) and medium to high.

To sum up, this shows that fatigue and fatigue management is considered poorest by pilots who work for Cargo and Low cost airlines and significantly more negative than pilots who work for other company

types.





Figure 45 Means for Fatigue by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo


/surveillance

Helicopter

General Aviation

Business/VIP/State

Fatigue




Speaking up

Post-hoc Games-Howell pairwise comparisons showed that Network pilots rated Speaking Up higher than Low cost and General aviation pilots.

The effect sizes for Network and Low cost (Cohen’s d = 0.186182) is low, and Network and General

aviation (Cohen’s d =0.744912.) is considered to be medium to high.

The mean difference for Network and Low cost (0.12267) is low, and Network and General aviation

(0.50595) is considered to be medium to high.

However, general Aviation pilots are often single pilot operations where ‘speaking up’ would not

applicable.


Figure 46 Means for Speaking Up by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo


General Aviation

Other (Pleasestate)

Business/VIP/State

Speaking up





Similar to the results found with Fatigue. Post-hoc Games-Howell pairwise comparisons showed that both Low cost and Cargo reported significantly lower scores on Perceived Organisational Support (POS) than

every other company type (General Aviation, Aerial work/ambulance/surveillance, Helicopter

Business/VIP/State, Charter/Leisure, Network). Business/VIP/State reported significantly higher scores on POS than Network.

The effect sizes for Low cost and General Aviation (Cohen’s d =0.927929), Low cost and Aerial

work/ambulance/surveillance (Cohen’s d =1.276184), Low cost and Helicopter (Cohen’s d = 0.695834), Low cost and Business/VIP/State (Cohen’s d =1.093989), Low cost and Charter/Leisure (Cohen’s d

=0.800569) are all high, and Low cost and Network (Cohen’s d =0.629447) is medium to high.

Cargo and General Aviation (Cohen’s d =0.798518), Cargo and Aerial work/ambulance/surveillance (Cohen’s d =1.156615), Cargo and Business/VIP/State (Cohen’s d = 0.965775) are all considered to be high.

Cargo and Charter/Leisure (Cohen’s d = 0.666153) is high to medium, and Cargo and Helicopter (Cohen’s d

=0.570162), and Cargo and Network (Cohen’s d = 0.491574) are medium.

Business/VIP/State and Network (Cohen’s d = 0.462671) is medium. The mean difference for Low cost and

General Aviation (-0.79545), Low cost and Aerial work/ambulance/surveillance (-1.13238), Low cost and

Business/VIP/State (-0.92274) are all high, Low cost and Helicopter (-0.63657), and Low cost and Charter/Leisure (-0.67141) and Low cost and Network (-0.52695) is medium to high.

Cargo and General Aviation (-0.67241), Cargo and Aerial work/ambulance/surveillance (-1.00934), Cargo

and Business/VIP/State (-0.79970) are all considered to be medium to high. Cargo and Charter/Leisure (-0.54838) is medium, and Cargo and Helicopter (-0.51353) are medium, and Cargo and Network (-0.40391)

is low to medium. Business/VIP/State and Network (0.52695) is medium.





Figure 47 Means for Perceived Organisational Support by Company type

1.001.502.002.503.003.504.004.505.00

Network

Low cost

Charter/leisure

Cargo

Aerialwork/ambulance/

surveillance

Helicopter

General Aviation

Business/VIP/State





3.4.3.2. Job title

Summary overview

The figure below plots all of the mean scores (and error bars) for each safety culture dimension according

to the job type of pilots.

Figure 48 Means and error bars for all dimensions by Job title

Overall, Captains had the most negative views and second officers held the most positive views, however

there was a small sample of second officers. Captains and First Officers opinions were more similar.




The table below reports the mean scores for each safety culture dimension according to the job title of

pilots.

Table 21 Mean scores by job type

Job type

Captain First Officer Second Officer Management Commitment to Safety 3.42 3.45 3.97

Collaboration & Involvement 3.59 3.61 3.86

Just Culture & Reporting 3.70 3.71 4.05

Communication & Learning 3.64 3.78 4.09

Risk Handling 3.75 3.79 4.01

Colleague Commitment 4.00 4.12 4.27

Staff Equipment 3.38 3.50 4.05

Procedures & Training 3.72 3.73 3.77

Fatigue 2.82 2.81 3.38

Speaking up 3.84 3.85 4.10

Perceived Organisational Support 2.65 2.65 3.49




Levene’s test of Homogeneity of Variance showed equal variance for all dimensions apart from

Communication & Learning, Risk Handling, Staff & Equipment and Speaking up.

ANOVA showed that there were significant differences for all dimensions apart from Procedures &

Training and Speaking up. Welch and Brown-Forsyth pairwise comparisons presented the same significant

results, but additionally found no significant difference between Collaboration & Involvement, Just Culture and Risk Handling.

Table 22 shows significant ANOVA results for all dimensions apart from the Procedures & Training

dimension.

Table 22 ANOVA overview of significant differences between groups for Job title



Between Groups 22.261 2 11.130 13.641 .000

Within Groups 5808.643 7119 .816

Total 5830.904 7121


Between Groups 5.693 2 2.847 6.651 .001

Within Groups 2921.557 6826 .428

Total 2927.250 6828


Between Groups 7.956 2 3.978 7.765 .000

Within Groups 3490.726 6814 .512

Total 3498.682 6816


Between Groups 41.889 2 20.944 36.050 .000

Within Groups 3961.102 6818 .581

Total 4002.991 6820

Risk Handling

Between Groups 6.625 2 3.312 6.714 .001

Within Groups 3383.648 6858 .493

Total 3390.273 6860


Between Groups 28.766 2 14.383 34.400 .000

Within Groups 2997.512 7169 .418

Total 3026.279 7171

Staff & Equipment

Between Groups 47.753 2 23.876 31.807 .000

Within Groups 5141.967 6850 .751

Total 5189.720 6852


Between Groups .515 2 .257 .930 .395

Within Groups 1885.132 6810 .277

Total 1885.647 6812

Fatigue

Between Groups 20.233 2 10.117 12.862 .000

Within Groups 5366.676 6823 .787

Total 5386.909 6825

Speaking up

Between Groups 4.037 2 2.018 4.521 .011

Within Groups 3040.338 6810 .446

Total 3044.375 6812


Between Groups 45.258 2 22.629 29.196 .000

Within Groups 5206.959 6718 .775

Total 5252.217 6720




Management commitment

Post-hoc Games-Howell pairwise comparisons showed that Second Officers reported significantly higher management commitment scores than Captains and First Officers at the .001 level of significance.

The effect sizes for Second and Captains (Cohen’s d =0.5954) and Second Officers and First Officers

(Cohen’s d =0.569214) are considered to be medium, based on statistical guidance (Cohen 1992).

The mean difference for Second Officers and Captains (0.55113) and Second Officers and First Officers (-

0.52026) are considered to be medium.

Figure 49 Means for Management Commitment to Safety by Job title

1.001.502.002.503.003.504.004.505.00

Captain

First OfficerSecond Officer






Post-hoc Games-Howell pairwise comparisons showed that Captains reported significantly lower Communication & Learning scores than First and Second Officers at the .001 level of significance.

The effect sizes for Captains and First Officers (Cohen’s d = 0.185369) is low and for Captains and Second

Officers (Cohen’s d = 0.554102.) is considered to be medium.

The mean difference for Captains and First Officers (-0.14033) is low and for Captains and Second Officers

(-0.44249) is considered to be medium.

Figure 50 Means for Communication & Learning by Job title

1.001.502.002.503.003.504.004.505.00

Captain







Post-hoc Games-Howell pairwise comparisons showed that Captains reported significantly lower Colleague Commitment scores than First Officers at the .001 level of significance.

The effect sizes for Captains and First Officers (Cohen’s d = 0.187682) is low.

Figure 51 Means for Colleague Commitment by Job title

1.001.502.002.503.003.504.004.505.00

Captain






Staff and Equipment

Post-hoc Games-Howell pairwise comparisons showed that Second Officers reported significantly higher Staff and Equipment scores than Captains and First Officers, and First Officers reported significantly higher

Staff and Equipment scores than Captains.

The effect sizes for Second Officer and Captains (Cohen’s d =0.73056), Second Officer and First Officers (Cohen’s d =0.620305) are considered to be quite high and First Officer and Captain (Cohen’s d

= 0.138603) to be low.

The mean difference for Second Officer and Captains (0.66700), Second Officer and First Officers (0.54761) are all considered to be medium to high and First Officer and Captain (0.11938) to be low.

Figure 52 Means for Staff & Equipment by Job title

1.001.502.002.503.003.504.004.505.00

Captain


Staff Equipment




Fatigue

Post-hoc Games-Howell pairwise comparisons showed that Second Officers reported significantly Fatigue scores than Captains and First Officers at the .001 level of significance.

The effect sizes for Second Officer and Captains (Cohen’s d = 0.578475) and Second Officers and First

Officers (Cohen’s d = 0.592116) are all considered to be medium.

The mean difference for Second Officer and Captains (0.56271) and Second Officers and First Officers

(0.57268) are considered to be medium.

Figure 53 Means for Fatigue by Job title

1.001.502.002.503.003.504.004.505.00

Captain


Fatigue





Post-hoc Games-Howell pairwise comparisons showed that Second Officers reported significantly Fatigue scores than Captains and First Officers at the .001 level of significance.

The effect sizes for Second Officer and Captains (Cohen’s d = 0.88641) and Second Officer and First

Officers (Cohen’s d =0.887179) are considered to be high.

The mean difference for Second Officer and Captains (0.84511) and Second Officer and Captains (0.84475)

are all considered to be high.

Figure 54 Means for Perceived Organisational Support by Job title

1.001.502.002.503.003.504.004.505.00

Captain


Perceived Organisational…




3.4.3.3. Management role

Summary overview


to whether they had a management role.

Figure 55 Means and error bars for all dimensions by Management Role

Pilots with a management role, either in operations, training or safety have a significantly more positive

perception that those who do not hold any management role, across a number of safety culture

dimensions. This may be because these pilots are potentially in a position of power to make changes to improve safety, therefore there may be self-desirability bias here. Alternatively, perhaps those in

management positions do not hear or witness as many operational problems, because they are hidden

from them, or it may reflect communication issues, i.e. pilots in management positions are more aware of the reasons behind changes to SOPs, and therefore understand them better.




The table below reports the mean scores for each safety culture dimension according to whether pilots

had management role.

Table 23 Mean scores by management role

Management role

Yes (flight operations

and training) Yes (safety

department)

Yes (other incl.

Union/Compnay Council) No

Management Commitment to Safety 3.64 3.71 3.48 3.41

Collaboration & Involvement 3.63 3.70 3.63 3.60

Just Culture & Reporting 3.78 3.84 3.81 3.70

Communication & Learning 3.72 3.84 3.82 3.70

Risk Handling 3.82 3.77 3.80 3.76

Colleague Commitment 4.01 3.94 4.17 4.06

Staff Equipment 3.48 3.57 3.50 3.43

Procedures & Training 3.81 3.72 3.73 3.72

Fatigue 3.01 3.21 2.89 2.79

Speaking up 3.81 3.65 3.98 3.86

Perceived Organisational Support 2.89 2.98 2.75 2.62




Levene’s Tests of Homogeneity of Variance were satisfied for all dimensions, apart from Speaking up.

ANOVA and Welch and Brown-Forsyth both found significant differences for Management Commitment, Procedures & Training, Fatigue and Perceived Organisational Support. Table 24 shows the ANOVA results.

Table 24 ANOVA overview of significant differences between groups for management role



Between Groups 41.660 3 13.887 17.107 .000

Within Groups 5778.957 7119 .812

Total 5820.617 7122


Between Groups 1.855 3 .618 1.447 .227

Within Groups 2918.153 6829 .427

Total 2920.008 6832


Between Groups 6.891 3 2.297 4.483 .004

Within Groups 3491.597 6814 .512

Total 3498.488 6817


Between Groups 2.764 3 .921 1.571 .194

Within Groups 4000.678 6819 .587

Total 4003.443 6822

Risk Handling

Between Groups 2.290 3 .763 1.547 .200

Within Groups 3384.730 6860 .493

Total 3387.020 6863


Between Groups 3.912 3 1.304 3.092 .026

Within Groups 3022.810 7169 .422

Total 3026.722 7172

Staff & Equipment

Between Groups 3.762 3 1.254 1.661 .173

Within Groups 5173.399 6851 .755

Total 5177.161 6854


Between Groups 5.304 3 1.768 6.423 .000

Within Groups 1873.812 6807 .275

Total 1879.116 6810

Fatigue

Between Groups 45.807 3 15.269 19.523 .000

Within Groups 5336.372 6823 .782

Total 5382.179 6826

Speaking up

Between Groups 6.295 3 2.098 4.703 .003

Within Groups 3037.140 6807 .446

Total 3043.435 6810


Between Groups 53.923 3 17.974 23.364 .000

Within Groups 5168.230 6718 .769

Total 5222.153 6721




1.001.502.002.503.003.504.004.505.00

Yes (flight operations& training)

Yes (safety)

Yes (other)

No



Post-hoc Games-Howell pairwise comparisons showed that pilots who hold a managerial position in flight operations or training reported significantly higher Management Commitment to Safety scores than pilots

with no managerial role at the .001 level of significance.

The effect sizes between Managerial role in flight operations or training and no managerial role groups (Cohen’s d = 0.258926) is considered to be low.

Figure 56 Means for Management Commitment by Management Role




1.001.502.002.503.003.504.004.505.00

Yes (flightoperations and

training)

Yes (safety)

Yes (other)

No



Post-hoc Games-Howell pairwise comparisons showed that pilots who hold a managerial position in flight operations or training reported significantly higher Procedures & Training to Safety scores than pilots with

no managerial role at the .001 level of significance.

The effect sizes between Managerial role in flight operations or training and no managerial role groups (Cohen’s d = 0.183197) is considered to be low.

Figure 57 Means for Procedures & Training by Management Role




Fatigue

Post-hoc Games-Howell pairwise comparisons showed that pilots who hold a managerial position in flight operations or training, or in the safety department, reported significantly higher (more positive) Fatigue

scores than pilots with no managerial role at the .001 level of significance.

The effect sizes between Managerial role in flight operations or training and no managerial role groups (Cohen’s d = 0.245071) is considered to be low, and between Managerial role in safety and no managerial

role groups (Cohen’s d = 0.481588) is medium.

Figure 58 Means for Fatigue by Management Role

1.001.502.002.503.003.504.004.505.00

Yes (flight operationsand training)

Yes (safety)

Yes (other)

No

Fatigue





Post-hoc Games-Howell pairwise comparisons showed that pilots who hold a managerial position in flight operations or training, or in the safety department, reported significantly higher Perceived Organisational

Support scores than pilots with no managerial role at the .001 level of significance.

The effect sizes between Managerial role in flight operations or training and no managerial role groups (Cohen’s d = 0.302861) is considered to be low, and between Managerial role in safety and no managerial

role groups (Cohen’s d = 0.42402) is between low and medium.

Figure 59 Means for Procedures & Training by Management Role

1.001.502.002.503.003.504.004.505.00

Yes (flightoperations and

training)

Yes (safety)

Yes (other)

No





3.4.3.4. Training background

Summary overview


to their training background.

Figure 60 Means and error bars for all dimensions by Training background (other not included)

Pilots that have had self-funded modular training generally have a significantly more negative perception

across dimensions compared with those with self-funded cadetship with an airline (integrated) training or

Airline funded cadetship.




The table below reports the mean scores for each safety culture dimension according to the training

background of pilots.

Table 25 Mean scores by training background

Training background

Military

Airline funded

cadetship

Self-funded cadetship,

with an airline

(integrated) training

Self-funded, modular training Other

University - State funded

Self-funded, self improver

(non-modular)

National flight school

- state funded

Management Commitment to Safety 3.47 3.43 3.54 3.39 3.49 3.61 3.25 3.53

Collaboration & Involvement 3.62 3.68 3.66 3.52 3.53 3.65 3.27 3.63

Just Culture & Reporting 3.73 3.82 3.77 3.61 3.71 3.88 3.54 3.74

Communication & Learning 3.68 3.89 3.79 3.58 3.61 3.80 3.44 3.76

Risk Handling 3.77 3.80 3.85 3.72 3.75 3.85 3.52 3.80

Colleague Commitment 4.03 4.18 4.12 3.98 3.87 4.18 3.70 4.03

Staff Equipment 3.46 3.54 3.52 3.32 3.52 3.56 2.86 3.58

Procedures & Training 3.73 3.69 3.77 3.73 3.70 3.87 3.48 3.76

Fatigue 2.91 2.94 2.87 2.69 2.81 2.96 2.30 2.99

Speaking up 3.80 3.94 3.95 3.78 3.64 3.96 3.80 3.80

Perceived Organisational Support 2.77 2.64 2.71 2.60 2.74 2.71 2.48 2.75




Levene’s Tests of Homogeneity of Variance were violated for all dimensions, apart from Procedures &

Training.

ANOVA and Welch and Brown-Forsyth both identified significant differences represented in all

dimensions. The table below shows the ANOVA results.

Table 26 ANOVA overview of significant differences between groups for training background



Between Groups 25.244 7 3.606 4.437 .000

Within Groups 5744.132 7067 .813

Total 5769.376 7074


Between Groups 35.272 7 5.039 11.899 .000

Within Groups 2869.157 6775 .423

Total 2904.430 6782


Between Groups 51.941 7 7.420 14.681 .000

Within Groups 3418.802 6764 .505

Total 3470.743 6771


Between Groups 114.969 7 16.424 28.794 .000

Within Groups 3859.862 6767 .570

Total 3974.830 6774

Risk Handling

Between Groups 17.368 7 2.481 5.041 .000

Within Groups 3350.828 6808 .492

Total 3368.196 6815


Between Groups 53.134 7 7.591 18.422 .000

Within Groups 2930.884 7113 .412

Total 2984.018 7120

Staff & Equipment

Between Groups 76.222 7 10.889 14.586 .000

Within Groups 5076.415 6800 .747

Total 5152.637 6807


Between Groups 7.308 7 1.044 3.792 .000

Within Groups 1860.072 6757 .275

Total 1867.380 6764

Fatigue

Between Groups 97.016 7 13.859 17.884 .000

Within Groups 5249.474 6774 .775

Total 5346.490 6781

Speaking up

Between Groups 44.416 7 6.345 14.414 .000

Within Groups 2973.636 6755 .440

Total 3018.053 6762


Between Groups 26.373 7 3.768 4.845 .000

Within Groups 5187.926 6672 .778

Total 5214.299 6679





Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through self-funded modular training reported significantly lower Management Commitment to Safety scores than pilots who

trained though a self-funded cadetship with an airline (integrated) training, at the .001 level of

significance.

The effect sizes between these two groups (Cohen’s d = 0.163361) is considered to be low.

Please see Appendix 3 Table 45 for percentage differences by training background per item.

Figure 61 Means for Management Commitment by Training background

1.001.502.002.503.003.504.004.505.00

Military

Airline fundedcadetship

Self-fundedcadetship, with an…

Self-funded,modular training

University - Statefunded

Self-funded, selfimprover (non-…

National flightschool - state…

Other






Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded modular training, reported significantly lower Collaboration & Involvement scores than pilots who trained

though an Airline funded cadetship and those who trained via a self-funded cadetship with an airline

(integrated) training, at the .001 level of significance.

The effect sizes between Airline funded cadetship and self-funded modular training (Cohen’s d =

0.250584), and between self-funded modular training and self-funded cadetship with an airline

(integrated) training (Cohen’s d = 0.200548) are considered to be low.


Figure 62 Means for Collaboration & Involvement by Training background

1.001.502.002.503.003.504.004.505.00

Military


Self-fundedcadetship, with anairline (integrated)…



Self-funded, selfimprover (non-

modular)

National flightschool - state

funded

Other





Just Culture

Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded modular training, reported significantly lower Collaboration & Involvement scores than pilots who trained


(integrated) training, at the .001 level of significance.

The effect sizes between Airline funded cadetship and self-funded modular training (Cohen’s d =

0.294639), and between self-funded modular training and self-funded cadetship with an airline

(integrated) training (Cohen’s d = 0.214277) are considered to be low.


Figure 63 Means for Just Culture by Training background

1.001.502.002.503.003.504.004.505.00

Military


Self-fundedcadetship, with anairline (integrated)

training

Self-funded, modulartraining



modular)

National flight school- state funded

Other






Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded modular training, reported significantly lower Communication & Learning scores than pilots who trained


(integrated) training, and those who trained at a National flight school that was state funded, all at the .001 level of significance. Pilots who trained via Airline funded cadetship had significantly higher scores

than those who learned to fly in the military.

The effect sizes between Airline funded cadetship and self-funded cadetship with an airline (integrated) training (Cohen’s d = 0.145553), and between Airline funded cadetship and National flight school (Cohen’s

d = 0.197043), and between Airline funded cadetship and Military training (Cohen’s d = 0.298874) are all

considered to be low.


Figure 64 Means for Communication & Learning by Training background

1.001.502.002.503.003.504.004.505.00

Military


Self-funded cadetship,with an airline





modular)

National flight school -state funded

Other





Risk Handling

Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through self-funded modular training reported significantly lower Risk Handling to Safety scores than pilots who trained

though a self-funded cadetship with an airline (integrated) training, at the .001 level of significance.

The effect sizes between these two groups (Cohen’s d = 0.176751) is considered to be low.


Figure 65 Risk Handling by Training background

1.001.502.002.503.003.504.004.505.00

Military






modular)

National flight school- state funded

Other

Risk Handling





Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded modular training, reported significantly lower Colleague Commitment scores than pilots who trained


(integrated) training, at the .001 level of significance. Pilots who trained via Airline funded cadetship had significantly higher scores than those who learned to fly in the military.

The effect sizes between self-funded modular training and self-funded cadetship with an airline

(integrated) training (Cohen’s d = 0.210317), and between a self-funded modular training and Airline funded cadetship (Cohen’s d = 0.313743), and between Airline funded cadetship and Military training

(Cohen’s d = 0.237097) are all considered to be low.


Figure 66 Means for Colleague Commitment by Training background

1.001.502.002.503.003.504.004.505.00

Military






modular)


funded

Other





Staff & Equipment

Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded modular training reported significantly lower Staff & Equipment scores than pilots who trained though an

Airline funded cadetship and those who trained via a self-funded cadetship with an airline (integrated)

training, and those who trained at a National flight school, all at the .001 level of significance.


(integrated) training (Cohen’s d = 0.216115), and between a self-funded modular training and Airline

funded cadetship (Cohen’s d = 0.256828), and between a self-funded modular training and National flight school (Cohen’s d = 0.302349) are all considered to be low.


Figure 67 Means for Staff & Equipment by Training background

1.001.502.002.503.003.504.004.505.00

Military


Self-fundedcadetship, with an

airline…




modular)


funded

Other

Staff Equipment





Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded cadetship with an airline (integrated) training reported significantly lower Procedures & Training scores

than pilots who trained though an Airline funded cadetship.

The effect sizes between self-funded cadetship with an airline (integrated) training and Airline funded cadetship (Cohen’s d = 0.163135) is considered to be low.


Figure 68 Means for Procedures & Training by Training background

1.001.502.002.503.003.504.004.505.00

Military



training




modular)


funded

Other





Fatigue

Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded modular training reported significantly lower (more negative) Fatigue management scores than pilots who

trained though an Airline funded cadetship and those who trained via a self-funded cadetship with an

airline (integrated) training, and those who trained at a National flight school, and who had Military training, all at the .001 level of significance.


(integrated) training (Cohen’s d = 0.196105), and between a self-funded modular training and Airline funded cadetship (Cohen’s d = 0.296761), and between a self-funded modular training and National flight

school (Cohen’s d = 0.352747), and between a self-funded modular training and Military training (Cohen’s

d = 0.246649) are all considered to be low.


Figure 69 Means for Fatigue by Training background

1.001.502.002.503.003.504.004.505.00

Military



training




modular)


funded

Other

Fatigue




Speaking Up

Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through a self-funded modular training reported significantly lower speaking up scores than pilots who trained though an Airline

funded cadetship and those who trained via a self-funded cadetship with an airline (integrated) training.

Whilst those that trained in the military reported significantly lower speaking up scores than pilots who trained though Airline funded cadetship and those who trained via a self-funded cadetship with an airline

(integrated) training, all at the .001 level of significance.

The effect sizes between self-funded modular training and self-funded cadetship with an airline (integrated) training (Cohen’s d =0.260041), and between a self-funded modular training and Airline

funded cadetship (Cohen’s d =0.248005), and between a Military training and self-funded cadetship with

an airline (integrated) training (Cohen’s d = 0.226), and between Military training and Airline funded cadetship (Cohen’s d = 0.213888) are all considered to be low.


Figure 70 Means for Speaking Up by Training background

1.001.502.002.503.003.504.004.505.00

Military



training




modular)


funded

Other

Speaking up





Post-hoc Games-Howell pairwise comparisons showed that pilots who trained to fly through self-funded modular training reported significantly lower Perceived Organisational Support scores than pilots who

trained in the military, at the .001 level of significance.

The effect sizes between these two groups (Cohen’s d = 0.190997) is considered to be very low.


Figure 71 Means for Perceived Organisational Support by Training background

1.001.502.002.503.003.504.004.505.00

Military



training




modular)


funded

Other





3.4.3.5. Contract type

Summary overview


to contract type of pilots. Appendix Table 39 presents the means for contract type by dimension.

Figure 72 Means and error bars for all dimensions by Contract type (other not included)

Pilots on a typical contract reported significantly higher scores than pilots on an atypical contract across

all but two (Management Commitment to Safety and Procedures and Training) safety culture dimensions.

This may be because those on an insecure contract are treated differently to those on a more secure

contract, as found elsewhere or that they perceive the organisation more negatively because of their lack of job security. It is notable that of those on an atypical contract, over a third (n=315) were pilots aged 30

or under. This group, in turn constituted only 15% of the sample (n=1082), which indicates new pilots

entering the industry are increasingly being employed on atypical contracts




Levene’s Tests of Homogeneity of Variance were satisfied for Management Commitment, Risk Handling,

and Procedures & Training.


An independent samples t-test showed no significant differences between those on a typical contract

(mean=3.44) compared with those on an atypical contract (mean=3.40) on their perceptions on Management Commitment to Safety at the .001 level of significance.

Please see Appendix 3 Table 44 for percentage differences by contract type per item.

Figure 73 Means for Management Commitment by Typical/Atypical Contract


An independent samples t-test showed that pilots on a typical contract (mean=3.62) reported significantly

higher Collaboration & Involvement scores than pilots on an atypical contract (mean=3.43), at the .001 level of significance.

The effect size (Cohen’s d= 0.355441) is low.


3.44

3.40

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical





Figure 74 Means for Collaboration & Involvement by Typical/Atypical Contract

Just culture


higher Just Culture scores than pilots on an atypical contract (mean=3.47), at the .001 level of

significance.



Figure 75 Means for Just Culture by Typical/Atypical Contract

3.62

3.43

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical


3.74

3.47

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical






An independent samples t-test showed that pilots on a typical contract (mean=3.74) reported significantly higher Communication & Learning scores than pilots on an atypical contract (mean=3.47), at the .001 level

of significance.



Figure 76 Means for Communication & Learning by Typical/Atypical Contract

Risk Handling

An independent samples t-test showed that pilots on a typical contract (mean=3.78) reported significantly higher Risk Handling scores than pilots on an atypical contract (mean=3.67), at the .001 level of

significance.


3.74

3.47

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical





Figure 77 Means for Risk Handling by Typical/Atypical Contract


An independent samples t-test showed that pilots on a typical contract (mean=4.09) reported significantly higher Colleague Commitment scores than pilots on an atypical contract (mean=3.83), at the .001 level of

significance. The effect size (Cohen’s d= 0.150524) is low.


Figure 78 Means for Colleague Commitment by Typical/Atypical Contract

3.78

3.67

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical

Risk Handling

4.09

3.83

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical





Staff & Equipment

An independent samples t-test showed that pilots on a typical contract (mean=3.46) reported significantly higher Staff & Equipment scores than pilots on an atypical contract (mean=3.26), at the .001 level of

significance.



Figure 79 Means for Staff & Equipment by Typical/Atypical Contract


An independent samples t-test showed no significant differences between those on a typical contract

(mean=3.73) compared with those on an atypical contract (mean=3.68) on their perceptions on

Procedures & Training at the .001 level of significance.


3.46

3.26

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical

Staff & Equipment




Figure 80 Means for Procedures & Training by Typical/Atypical Contract

Fatigue


higher Fatigue scores than pilots on an atypical contract (mean=2.49), at the .001 level of significance.



Figure 81 Means for Fatigue by Typical/Atypical Contract

3.73

3.68

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical


2.86

2.49

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical

Fatigue




Speaking up

An independent samples t-test showed that pilots on a typical contract (mean=3.87) reported significantly higher Speaking up scores than pilots on an atypical contract (mean=3.69), at the .001 level of

significance.



Figure 82 Means for Speaking Up by Typical/Atypical Contract

3.87

3.69

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical

Speaking up





An independent samples t-test showed that pilots on a typical contract (mean=2.68) reported significantly higher Perceived Organisational Support scores than pilots on an atypical contract (mean=2.41), at the

.001 level of significance.



Figure 83 Means for Perceived Organisational Support by Typical/Atypical Contract

3.4.3.6. Gender

T test pairwise comparisons showed no significant differences between males and females on their perceptions on any of the dimensions at the .001 level of significance.

2.68

2.41

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Typical

Atypical





3.4.3.7. Part-time/year & Full-time/year

Summary overview

The figure below plots all of the mean scores (and error bars) for each safety culture dimension according to whether they were full or part-time.

Figure 84 Means and Error bars for all dimensions by Part-time/year & Full-time/year

Overall, those on a part-time or part-year contract had more positive views than those on a full-time

contract. This contrasts the results for typical and atypical contract types, where atypical contracts had more negative views. Pilots may be on a permanent contract but work fewer hours and consequently may

be less involved with cultural issues than those on a full-time/full-year basis.




Levene’s Tests of Homogeneity of Variance were satisfied for all dimensions other than Just Culture,

Communication & Learning, Fatigue and Speaking up.


An independent samples t-test showed that pilots on a part-time or part-year contract (mean=3.47) reported significantly higher Management Commitment scores than pilots on a full-time contract

(mean=3.43) at the .001 level of significance.

The effect size (Cohen’s d= 0.043037.) is very low.

Figure 85 Means for Management Commitment by Part-time/year and Full time

3.47

3.43

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time





Just culture

An independent samples t-test showed that pilots on a part-time or part-year contract (mean=3.78) reported significantly higher Just Culture scores than pilots on a full-time contract (mean=3.69) at the



Figure 86 Means for Just Culture by Part-time/year and Full time

3.78

3.69

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time






An independent samples t-test showed that pilots on a part-time or part-year contract (mean=3.81) reported significantly higher Communication & Learning scores than pilots on a full-time contract



Figure 87 Means for Communication & Learning by Part-time/year and Full time

3.81

3.68

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time






An independent samples t-test showed that pilots on a part-time or part-year contract (mean=4.13) reported significantly higher Colleague Commitment scores than pilots on a full-time contract


The effect size (Cohen’s d= 0.139227) is very low.

Figure 88 Means for Colleague Commitment by Part-time/year and Full time

4.13

4.04

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time





Staff & Equipment

An independent samples t-test showed that pilots on a part-time or part-year contract (mean=3.51) reported significantly higher Staff & Equipment scores than pilots on a full-time contract (mean=3.42) at

the .001 level of significance.


Figure 89 Means for Staff & Equipment by Part-time/year and Full time

3.51

3.42

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time

Staff & Equipment




Fatigue

An independent samples t-test showed that pilots on a part-time or part-year contract reported (mean=2.91) significantly higher Fatigue scores than pilots on a full-time contract (mean=2.80) at the .001

level of significance.


Figure 90 Means for Fatigue by Part-time/year and Full time

2.91

2.80

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time

Fatigue




Speaking up

An independent samples t-test showed that pilots on a part-time or part-year contract (mean=3.91) reported significantly higher Speaking up scores than pilots on a full-time contract (mean=3.83) at the



Figure 91 Means for Speaking Up by Part-time/year and Full time

3.91

3.83

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time

Speaking up





An independent samples t-test showed that pilots on a part-time or part-year contract (mean=2.73) reported significantly higher Perceived Organisational Support scores than pilots on a full-time contract



Figure 92 Means for Perceived Organisational Support by Part-time/year and Full time

2.73

2.63

1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00

Part-time/year

Full-time





3.4.4. Correlations

A number of correlations were performed in order to examine whether responses to the safety culture

survey were associated with perceptions of safety culture. Correlations were performed for Age, Tenure, Flying Experience are reported through Spearman’s Rho Tests. Only the significant differences are

described.

3.4.4.1. Age

Spearman’s correlations show a negative correlation between age and Procedures & Training (rs=-0.48,

p<0.001), and Speaking Up (rs=-.043, p<0.001). This means that the older the pilot the more negative his/her views on these procedures and training and on speaking up. However, these have a low effect

size.

There was a positive correlation between age and Fatigue (rs =.054, p<0.001), and Perceived Organisational Support (rs=.061, p<0.001). This means that the older the pilot the more positive their

views on fatigue levels/management and organisational support. These have moderate effect sizes. All

other correlations were not significant. This reveals age not to be a factor across the dimensions.

3.4.4.2. Tenure

Spearman’s correlations show a negative correlation between tenure and Procedures & Training (rs=-.049, p<0.001). This means that the longer the pilot has worked within their organisation, the more negative

their opinions on procedures. There was a positive correlation between tenure and Just Culture (rs=.048,

p<0.001) and Fatigue (rs=.044, p<0.001). This means those who have been in the organisation longer hold more positive views on just culture and fatigue management. These all have moderate effect sizes. All

other correlations were not significant.

3.4.4.3. Flying experience


Pearson correlations show a negative correlation between flying experience and Management

Commitment (rs=-.044, p<0.001). This means that the more hours the pilot has flown, the more negative

their opinions on management commitment to safety. This has a medium effect size.


Pearson correlations show a negative correlation between flying experience and Procedures & Training (rs=-.068, p<0.001). This means that the more hours the pilot has flown, the more negative their opinions

on procedures and training. This has a good effect size.




3.4.4.4. Safety Culture Dimension Means by Company

To examine further the variations in safety culture amongst pilots, we explored whether pilots who

reported working at different companies had diverging perceptions of safety culture. It was found that for some safety culture dimensions, scores across companies were relatively similar, and positive. However

for others, scores were divergent and heterogeneous. Please note, companies are anonymised, and

company numbers do not map onto a single company. To support interpretation, the two lines on the graph indicate where means are either <=2.5 or >= 3.5.

The figure below reports on Management Commitment to Safety. It can be seen that the most positive

company mean is 4.31 and the lowest company mean at 2.40.

Figure 93 Means for Management Commitment to Safety by company (for companies with =>30 respondents)




The figure below reports on Collaboration and Involvement. It can be seen that the most positive

company mean is 4.08 and the lowest company mean at 2.86.

Figure 94 Means for Collaboration and Involvement by company (for companies with =>30 respondents)

The figure below reports on Just Culture and Reporting. It can be seen that 46 percent of company mean scores were above 3.5, and the range was 2.81 to 4.24.

Figure 95 Means for Just Culture and Reporting by company (for companies with =>30 respondents)




The figure below reports on Communication and Learning. It can be seen that the most positive company

mean is 4.28 and the lowest company mean at 2.86.

Figure 96 Means for Communication and Learning by company (for companies with =>30 respondents)

The figure below reports on Risk Handling. It can be seen that the most positive company mean is 4.25

and the lowest company mean at 3.19.

Figure 97 Means for Risk Handling by company (for companies with =>30 respondents)




The figure below reports on Colleague Commitment to Safety. It can be seen that the most positive

company mean is 4.48 and the lowest company mean at 3.39. Overall, 94% of companies had a mean score above 3.5.

Figure 98 Means for Colleague Commitment to Safety by company (for companies with =>30 respondents)

The figure below reports on Staff and Equipment. It can be seen that the most positive company mean is 4.26 and the lowest company mean at 2.72. Overall, 50% of companies had a mean score below 3.5.

Figure 99 Means for Staff & Equipment by company ID (for companies with =>30 respondents)




The figure below reports on Procedures and Training. It can be seen that the most positive company mean

is 4.27 and the lowest company mean at 3.46.

Figure 100 Means for Procedures and Training (for companies with =>30 respondents)

The figure below reports on Fatigue. It can be seen that the most positive company mean is 3.81 and the

lowest company mean at 2.01.

Figure 101 Means for Fatigue (for companies with =>30 respondents)




The figure below reports on Speaking-up. It can be seen that the most positive company mean is 4.29 and

the lowest company mean at 3.11.

Figure 102 Means for Speaking Up (for companies with =>30 respondents)

The figure below reports Perceived Organisational Support. Forty percent of company mean scores were

below 2.5, and the range was 1.88 to 3.80.

Figure 103 Means for Perceived Organisational Support by company (for companies with =>30 respondents)




The table below reports on the proportion of companies, by safety culture dimension, with mean scores

of 2.5 or lower, between 2.5 and 3.5, and 3.5 or above. Overall, it was found that companies which were low on one safety culture dimension (e.g. fatigue) tended to be low on others.

Table 27 Means for Perceived Organisational Support by Company ID (for companies with =>30 respondents)

Safety Culture Dimension % of companies with a mean score of <=2.5

% of companies with a mean score of >2.5 to <3.5

% of companies with a mean score of >=3.5

Management commitment to safety 3 50 47 Collaboration and Involvement 0 38 62 Just Culture and Reporting 0 19 81 Communication and Learning 0 25 75 Risk Handling 0 16 84 Colleague commitment to safety 0 6 94 Staff and equipment 0 50 50 Procedures & Training 0 9 91 Fatigue 25 69 6 Speaking up 0 22 78 Perceived Organisational Support 41 53 6

The above analysis indicates considerable variations in perceptions of safety culture dimensions between

pilots working at different companies. This indicates that safety practices at aviation companies differ, leading to differential beliefs on issues such as the extent to which management is committed to safety,

or resourcing. However, because this survey did not set out to survey safety culture in individual

companies, which would achieve more complete samples per company, the evidence for this finding could be strengthened through engagement with individual airlines.




3.4.4.5. Safety Culture Dimension Means by Nationality and Country Base

To examine further the variations in safety culture amongst pilots, we also focussed on the nationality of

pilots and the country where they were based. To present the data, it was necessary to focus only on nationalities with over 100 pilots.

The table below reports on safety culture dimensions by pilot nationality. It can be seen that there is

relatively little variance between pilots of different nationality.

Table 28 Perceptions of safety culture by nationality


to Safety




Risk Handling

Colleague commitment

to safety

Staff & Equipment


Fatigue Speaking up Perceived

Organisational Support

Austrians 3.55 3.60 3.74 3.74 3.80 4.11 3.41 3.83 2.87 3.86 2.56

Belgians 3.14 3.43 3.35 3.32 3.68 3.84 3.14 3.68 2.47 3.81 2.36

Danes 3.60 3.64 3.75 3.65 3.86 4.09 3.36 3.72 2.74 4.07 2.69

Dutch 3.80 3.86 3.96 3.95 4.05 4.20 3.83 3.96 3.27 4.09 3.26

Finns 3.69 3.82 3.98 3.77 3.93 4.22 3.34 3.63 2.77 3.76 2.56

French 3.32 3.51 3.57 3.67 3.74 3.91 3.50 3.64 2.84 3.56 2.51

German 3.34 3.61 3.75 3.85 3.77 4.16 3.50 3.73 2.92 3.90 2.57

Irish 3.43 3.62 3.65 3.64 3.76 3.99 3.29 3.75 2.44 3.85 2.51

Italian 3.21 3.37 3.37 3.33 3.59 3.69 3.16 3.58 2.66 3.47 2.54

Luxembourgers

3.08 3.47 3.44 3.54 3.73 3.96 3.00 3.74 2.49 4.00 2.40

Norwegian 3.68 3.80 3.83 3.77 3.81 4.32 3.64 3.93 3.01 4.03 2.88

Portuguese 3.72 3.59 3.68 3.65 3.79 4.09 3.66 3.97 3.14 3.49 2.95

Spaniards 3.09 3.24 3.28 3.35 3.45 3.63 3.07 3.59 2.48 3.31 2.40

Swedes 3.57 3.65 3.83 3.69 3.79 4.15 3.44 3.74 2.79 4.01 2.60

Swiss 3.47 3.83 3.86 3.98 3.81 4.22 3.59 3.60 2.96 4.02 2.84

United Kingdom 3.23 3.39 3.58 3.41 3.61 3.94 3.05 3.52 2.35 3.88 2.32




Similarly, the table below reports on safety culture dimensions by the country at which pilots are based.

Table 29 Perceptions of safety culture by the country at which pilots are based.

Management commitment

to safety




Risk Handling

Colleague commitmen

t to safety

Staff & equipment

Procedures & Training Fatigue Speaking up

Perceived Organisational

Support

Austria 3.56 3.49 3.73 3.56 3.84 3.91 3.35 3.76 2.80 3.58 2.55

Belgium 3.20 3.41 3.34 3.23 3.66 3.78 3.14 3.75 2.43 3.78 2.32

Croatia 3.11 3.34 3.54 3.63 3.53 3.85 3.16 3.99 2.35 3.45 2.31

Denmark 3.80 3.76 3.95 3.80 3.94 4.24 3.47 3.73 2.96 4.21 2.89

Estonia 3.25 3.56 3.61 4.06 3.67 3.78 3.56 4.00 2.78 3.67 2.75

Finland 3.63 3.83 3.98 3.80 3.92 4.23 3.31 3.63 2.79 3.78 2.61

France 3.29 3.52 3.57 3.70 3.72 3.89 3.53 3.63 2.90 3.52 2.56

Germany 3.35 3.61 3.76 3.86 3.77 4.16 3.51 3.72 2.92 3.92 2.57

Iceland 4.09 3.81 4.10 4.03 4.01 4.24 3.89 4.00 3.31 3.97 3.22

Ireland 3.40 3.65 3.65 3.67 3.77 3.98 3.31 3.76 2.41 3.87 2.51

Italy 3.18 3.35 3.35 3.27 3.65 3.68 3.16 3.61 2.50 3.53 2.40

Luxembourg 2.74 3.43 3.09 3.32 3.63 3.85 2.82 3.82 2.30 3.86 2.16

Netherlands 4.00 3.97 4.11 4.10 4.13 4.30 4.04 4.01 3.55 4.17 3.57

Norway 3.66 3.77 3.80 3.75 3.79 4.31 3.63 3.93 2.98 4.04 2.84

Portugal 3.66 3.59 3.66 3.58 3.80 4.06 3.58 3.96 2.97 3.55 2.79

Spain 3.21 3.30 3.36 3.37 3.56 3.71 3.11 3.65 2.44 3.49 2.29

Sweden 3.62 3.71 3.89 3.72 3.79 4.19 3.47 3.75 2.82 4.03 2.62

Switzerland 3.49 3.80 3.88 3.99 3.78 4.25 3.61 3.61 2.98 4.02 2.89

United Kingdom 3.27 3.41 3.60 3.43 3.63 3.97 3.06 3.52 2.40 3.90 2.36

Other 3.33 3.41 3.51 3.51 3.54 3.81 3.29 3.65 2.73 3.45 2.65

There were minimal differences in responses from pilots across the different European countries and

across different nationalities.




3.4.5. Comparison with ATM (a comparison with published data)

A comparisons between previously been tested in Air Traffic Management (operational staff only) across

Europe (n=5,176)(Reader, Noort et al. 2015) compared with pilot mean scores on the same dimensions from this study (n=7,329) shows similar safety culture means (see Figure 104). Not all dimensions had the

same items and two of the dimensions we have matched are have different names Procedures & Training

and Safety Support, so a statistical test of differences is not presented. As can be seen below, the data from pilots is broadly equivalent to ATM.

Figure 104 Comparison t-test between pilots and ATM

Managementcommitment

to safety

Collaborationand

Involvement

Just Cultureand Reporting

Communication and

Learning

Colleaguecommitment

to safety


ATM 3.48 3.37 3.14 3.22 3.99 3.31

Airlines 3.44 3.60 3.71 3.71 4.06 3.73

0.00

1.00

2.00

3.00

4.00

5.00

Mea

n




4 DISCUSSION AND LIMITATIONS

4.1. Discussion

According to the Civil Aviation Authority, a positive safety culture is the foundation to an effective safety

management system (CAA, 2015). In this study, we measured perceptions of safety culture amongst 7,239 pilots working in Europe. This is equivalent to approximately 14% of the population, and one of the largest

ever safety culture studies of pilots working in commercial aviation.

Overall, perceptions of safety culture amongst pilots working in Europe were favourable, although differences were found according to the contracts and companies pilots worked for. For the majority of

items (59%) responses to the survey were above 3.5 (indicating mostly positive perceptions). For example,

pilots were very positive on issues such as the SOPs associated with their work, the ability of their colleagues, being able to speak to their manager if an unsafe situation develops, and not feeling under

pressure to take risks that make them feel uncomfortable. For 41% of items, scores were below 3.5,

indicating mixed or negative perceptions. For example, in terms of feeling tired, getting feedback on safety issues, communication on safety, and training. In terms of safety culture dimensions, which are

used to characterise the culture, the mean scores of 7 dimensions were above 3.5. Four dimensions were

between 2.5 and 3.5. This indicates that whilst safety culture is generally perceived positively by pilots, some attention is required.

In terms of safety culture dimensions, pilots tended to have concerns over the issues of fatigue and

fatigue management, management commitment to safety, staff and equipment, and perceived organisational support. At an individual survey item level, concerns focussed on trust in management with

regard to safety, receiving feedback on safety issues, training, national aviation authorities, and pilots

being tired at work. More positively, the vast majority of pilots felt their colleagues were committed to safety, that voicing concerns on safety was encouraged, and that they do not need to take risks that make

them feel uncomfortable about safety.

Between group analyses revealed that the extent to which pilots had positive or negative perceptions of safety culture was, in-part, influenced by the type of company they worked for (e.g. Cargo, Low Cost,

Network Carrier), and their contract with that company (e.g. typical or atypical). In general, those at Low

Cost and Cargo companies, and on atypical contracts, tended to view safety culture least positively. It is notable that most pilots (88.47%) were on typical contracts. However, of those on an atypical contract,

over a third (n=315) were pilots aged 30 or under. This group, in turn constituted only 15% of the sample

(n=1082), which indicates new pilots entering the industry are increasingly being employed on atypical contracts, with potential implications for safety culture. This is consistent with research on the changing

nature of Pilot employment contracts5.

5 Jorens, Y., Gillis, D., Valcke, L., & De Coninck, J. ‘Atypical Forms of Employment in the Aviation Sector’, European Social Dialogue, European Commission, 2015.




Analysis showed considerable variation, for some safety culture dimensions, between pilots working at

different companies. This indicates that safety practices at aviation companies differ, leading to differential beliefs on issues such as the extent to which management is committed to safety, or

resourcing.

4.2. Limitations

Despite a number of security checks to capture bogus entries, pilots completed the survey anonymously,

meaning it is not possible to identify their credentials or the companies they reported working for.

Because this survey did not set out to survey safety culture in any particular company, data relating to individual companies must be interpreted with caution. However, data analysis indicates that pilots were

not uniform in the nature of their response patterns. They were positive on some issues, and negative on

others. Furthermore, responses to survey items within a psychometric dimension tended to be consistent with one another. This indicates that pilots were completing the survey in the expected fashion, and that

the survey was not being used to air grievances.

Data analysis using higher-level statistics has yet to be performed (e.g. confirmatory factor analysis, multi-

level modelling), and this report is primarily descriptive. A number of issues in the data arose around

variance and group sizes. Simply put, group sizes (e.g. within contract types) were unequal, albeit taken into account within the statistical tests. Furthermore, some of the between group comparisons showed

weak effect sizes (indicated differences between groups were low in some cases).

The survey was heavily distributed through the European Cockpit Association and their trade members.

Another approach could directly survey pilots through their airlines. However, efforts were made to

advertise through other methods including social media and resulted in a very large sample (14% of the population). The sample largely comprised of Northern and Western European countries.




5 CONCLUSIONS AND RECOMMENDATIONS

5.1. Conclusions

This is the first major independent survey of the safety culture of European pilots, achieving a return rate

of more than 7000 pilots. The results show that the overall pilots’ perception of safety culture is generally positive. However, the survey also reveals significant differences in the pilots’ assessment of safety

culture depending on different factors such as the type of airlines they work for or the type of contracts

on which they operate. Pilots working on atypical contracts and those working for low cost and cargo airlines have more negative perceptions of safety culture than their colleagues working under more

secure forms of employment and for network carrier airlines. Perceptions of management commitment to

safety, staffing and equipment, fatigue and perceived organisational support were not especially positive across the whole sample.

Aviation has the reputation of being the safest mode of transport, and indeed other modes of transport

(rail, road and sea) look to aviation to learn how to do safety better. This survey represents a significant learning opportunity for the aviation industry, to reflect on why it is so safe, and also where it needs to

address certain issues to ensure that it continues to remain so safe in the future.

5.2. Recommendations

Going forward, researchers and safety practitioners may wish to focus on the following. First, to identify

the causes and potential solutions on the areas of safety culture within European aviation that were less

positively perceived by pilots in this survey (e.g. fatigue, management commitment to safety). Second, and as done in other safety critical industries (ATM, Oil and Gas), to begin systematically measuring and

exploring safety culture in commercial aviation companies. Third, to consider opportunities for inter-

organisational learning on safety culture (e.g. sharing best practice amongst organisations).

Overall, our results were consistent with some of the previous research in the commercial aviation sector.

For example, on the notion that company variations have an influence upon the safety culture of pilots

(Evans, Glendon et al. 2007). Nevertheless, for the first time across the European industry, safety culture amongst pilots has been systematically measured. This creates data for ‘normalising’ what safety culture

looks like from the perspective of pilots (e.g. for comparable future studies), and provides a survey scale

for future studies to use.

The industry and its constituents, from the airlines to the regulators, and even the European Commission,

need to consider the results in this report. Overall there is much to be positive about, however there are

concerns that require consideration. Four ways forward are suggested:

1. One is to convene a series of workshops with pilots, managers and decision makers, to discuss the

results and what is beneath them, i.e. what is driving these results, and what could be changed

that would bolster safety culture yet still enable European aviation to remain competitive. Such




workshops would need representation from Low Cost and Cargo airlines, as well as companies

and staff utilising atypical contracts.

2. The results of the survey indicate that pilots across the industry are concerned with fatigue

management. Over half did not believe their company takes fatigue seriously. This needs to be

addressed by actions undertaken jointly with regulators, airlines and representative bodies, to educate managers and pilots about the potential safety implications and also the necessity to

improve this cultural dimension.

3. Given the different perception of safety culture according to the type of contracts under which pilots work, the regulatory authorities should consider how to take this factor into account to

ensure the continued safety of operations. The results from this survey raise questions about the

potential impact on safety culture of atypical contracts.

4. On a more strategic level, commercial aviation, as is done in other safety critical industries (e.g.

ATM, Oil and Gas), needs to begin systematically measuring and exploring safety culture in

commercial aviation companies. This is also beginning within the Future Sky Safety programme of work, with several airlines are already embarking on specific safety culture studies. This approach

allows the management of such companies, as well as other staff besides pilots, to have their say.

If this is achieved, learning on safety culture (e.g. sharing best practices amongst organisations) can begin to occur across European airlines as it already occurs for Air Traffic Management

organisations.




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7 APPENDICES

7.1. Appendix 1 Demographic group cross-tabulations

A number of cross-tabulations were conducted. This was in order to examine in greater depth the demographic categories of respondents.

The table below shows that 39.18% of 18-30 year old pilots were on atypical contracts, in comparison to 11.91% of 18-30 year olds on a typical (permanent) contract.

Table 30 Contract Type and Age

Age

Total 18-30 31-40 41-50 51-60 60+

Contract type

Typical contract 759 1927 2180 1331 178 6375

Atypical contract 315 226 141 84 38 804

Total 1074 2153 2321 1415 216 7179

The table below shows that the majority of pilots with typical contracts were based in Network airlines

(62.30%), whilst only 17.42% of employees at network airlines were on atypical contracts. The majority of pilots with atypical contracts worked for Low cost airlines (60.40%).

Table 31 Contract Type and Company Type

Company type

Network Low cost

Charter/

leisure Carg

o

Aerial work/ambulance

/surveillance Helicopte

r General Aviation

Business/VIP/State Total

Contract Type

Typical contract 3972 1246 489 419 34 92 39 85 6376

Atypical contract 139 482 49 28 17 21 31 31 798

Total 4111 1728 538 447 51 113 70 116 7174




The table below shows that over half (64%) of network pilots had been in their organisation for 11 or

more years. This is unlike low cost airlines, where 43% of pilots have worked for 4 or fewer years. 30% of charter/leisure pilots had worked for their airline for 4 or fewer years, and the majority (81%) of cargo

pilots had worked for their company for 5 or more years.

The table below shows that almost 80% (77.18%) of pilots on typical contracts have over 5000+ hours, whilst 43.73% of those on atypical contracts have flown less than 3000 hours.

Table 32 Contract type and Flying Experience

Flying experience (flight hrs) Total

<1000 1000-3000 3001-5000 5001-10000 10000+

Contract Type

Typical contract 79 504 874 1925 3002 6384

Atypical contract 115 237 131 162 160 805

Total 194 741 1005 2087 3162 7189

The table below shows that a little over half (52.20%) of pilots on an atypical contract, and 41.25% of

those on typical contracts had self-funded modular training.

Table 33 Contract type and Training background

Training background

Total

Military

Airline funded

cadetship


with an airline




Self-funded,

self improver

(non-modular)

National flight

school - state

funded

Contract Type Typical contract 711 1602 1042 2603 44 35 17 257 6311

Atypical contract 78 82 166 416 7 6 5 37 797

Total 789 1684 1208 3019 51 41 22 294 7108




The table below shows that the majority of pilots working for Network airlines, Charter, Helicopter, Aerial

work/ambulance/surveillance and Cargo have had a tenure of 11 years or over, whilst those working for

Low cost, Business/VIP/State airlines and general aviation have more of an equal split majority between

tenures of 1-4yrs and 5-10yrs.

Table 34 Company Type and Tenure

Company type

Network

Low cost

Charter/leisure Cargo

Aerial work/ambulance/surveillanc

e Helicopte

r

General Aviatio

n Business/VIP/State Total

Tenure

<1yr 126 107 29 15 8 5 13 14 317

1-4yrs 402 640 138 67 16 27 27 46 1363 5-10yrs 946 648 172 157 9 32 20 40 2024

11yrs+ 2637 342 205 208 18 49 15 16 3490

Total 4111 1737 544 447 51 113 75 116 7194

The table below shows that for most company types (excluding general aviation and Aerial work/ambulance/surveillance), over half of pilots had over 5000 hours of flying experience.

Table 35 Company type and Flying Experience

Flying experience (flight hrs)

<1000 1000-3000 3001-5000 5001-10000 10000+ Total

Company type

Network 69 272 470 1110 2199 4120

Low cost 71 312 313 531 509 1736 Charter/leisure 18 58 81 164 222 543

Cargo 3 26 64 171 182 446 Aerial work/ambulance/surveillance 7 8 14 18 3 50

Helicopter 7 20 29 42 15 113

General Aviation 17 16 12 17 13 75 Business/VIP/State 9 26 23 33 25 116

Total 201 738 1006 2086 3168 7199




The table below shows that a little over half (56.99%) of pilots from Network airlines, and 31.59% of those

from Low cost airlines had self-funded modular training.

Table 36 Company type and Training background

Training background Total

Military

Airline funded

cadetship


with an airline


Self-funded, modular training


Self-funded,

self improver

(non-modular)

National flight

school - state

funded Other

Company type

Network 496 1390 635 1284 25 8 194 32 4064

Low cost 114 156 373 982 12 13 63 10 1723

Charter/leisure 45 69 98 310 3 0 10 5 540

Cargo 50 53 80 251 1 1 6 3 445

Aerial work/ambulance/surveillance 15 0 0 29 0 0 6 0 50

Helicopter 43 10 10 43 0 0 2 0 108

General Aviation 12 4 6 44 0 0 4 1 71

Business/VIP/State 17 4 10 77 0 0 8 0 116

Total 792 1686 1212 3020 41 22 293 51 7117

The table below shows that for pilots over 51, at least 25% were trained in the military, at least 25% were

trained through airline cadetship, and 5% or less were self-funded (with airline training). Of those under

40, over 22% were self-funded (with airline training), and only 4% trained in the military. For those

between 41-50, nearly half (46%) were self-funded (with modular training).

Table 37 Age and Training background

Age

18-30 31-40 41-50 51-60 60+ Total

Training background

Military 10 67 269 374 71 791 Airline funded cadetship 243 481 560 346 55 1685

Self-funded cadetship, with an airline (integrated) training 354 497 288 71 4 1214 Self-funded, modular training 373 1003 1060 516 74 3026

Other 5 8 14 19 6 52

University - State funded 11 10 12 8 1 42 Self-funded, self improver (non-modular) 1 3 3 12 3 22

National flight school - state funded 74 63 95 52 11 295

Total 1071 2132 2301 1398 225 7127




7.2. Appendix 2 Means for dimensions by demographic groups

The tables below show the means for dimensions by demographic groups.

Table 38 Means for dimensions by demographic groups (Job title; Gender; Flying experience; Age; Tenure)

Job ttle Gender Flying experience Age Tenure

Dimension Captain First

Officer Second Officer Male Female <1000

1000-3000

3001-5000

5001-10000 10000+ 18-30 31-40 41-50 51-60 60+ <1yr 1-4yrs 5-10yrs 11yrs+


3.42 3.45 3.97 3.44 3.48 3.82 3.63 3.42 3.35 3.44 3.57 3.36 3.41 3.51 3.49 3.83 3.50 3.29 3.47

Collaboration & Involvement 3.59 3.61 3.86 3.60 3.63 3.76 3.64 3.57 3.57 3.61 3.65 3.56 3.58 3.65 3.62 3.77 3.57 3.53 3.64

Just Culture & Reporting 3.70 3.71 4.05 3.71 3.67 3.88 3.76 3.66 3.65 3.74 3.76 3.65 3.69 3.79 3.73 3.91 3.67 3.60 3.77

Communication & Learning 3.64 3.78 4.09 3.70 3.78 4.05 3.82 3.67 3.66 3.71 3.78 3.68 3.68 3.73 3.73 3.93 3.71 3.58 3.76

Risk Handling 3.75 3.79 4.01 3.77 3.81 4.00 3.85 3.72 3.74 3.77 3.85 3.72 3.76 3.79 3.75 3.96 3.78 3.69 3.79


4.00 4.12 4.27 4.05 4.14 4.13 4.10 4.07 4.03 4.06 4.10 4.05 4.03 4.08 4.03 4.12 4.03 4.00 4.09

Staff Equipment 3.38 3.50 4.05 3.44 3.42 3.78 3.59 3.40 3.36 3.44 3.57 3.36 3.41 3.50 3.46 3.72 3.42 3.32 3.48

Procedures & Training 3.72 3.73 3.77 3.73 3.74 3.86 3.81 3.78 3.70 3.70 3.81 3.72 3.71 3.70 3.74 3.79 3.78 3.72 3.71

Fatigue 2.82 2.81 3.38 2.82 2.77 3.09 2.84 2.76 2.77 2.84 2.83 2.74 2.81 2.91 2.99 3.09 2.78 2.68 2.89

Speaking up 3.84 3.85 4.10 3.85 3.87 3.86 3.88 3.87 3.81 3.86 3.92 3.85 3.81 3.86 3.82 3.81 3.83 3.80 3.89


2.65 2.65 3.49 2.65 2.67 3.10 2.74 2.61 2.58 2.67 2.69 2.55 2.65 2.75 2.92 3.13 2.67 2.51 2.69




Table 39 Means for dimensions by demographic groups (Company type; Contract type; Part-time or Part Year working; Part-timers average percentage work time)

Company type Contract type

Part-time or Part Year working

Part-timers average percentage work time

Dimension Network Low cost

Charter/leisure Cargo

Aerial work/ambulance/surveillanc

e Helicopter General Aviation

Business/VIP/State Other

Typical contract

Atypical contract

Other Yes No <25%

25-50%

51-75%

76-90%

91-100%


3.56 3.23 3.54 2.96 3.64 3.38 3.57 3.59 4.00 3.44 3.40 3.79 3.47 3.43 3.62 3.40 3.30 3.55 3.44




3.88 3.37 3.78 3.41 3.66 3.68 3.48 3.64 4.00 3.74 3.47 3.59 3.81 3.68 3.80 3.46 3.62 3.89 3.90

Risk Handling 3.83 3.68 3.78 3.65 3.65 3.47 3.47 3.70 2.67 3.78 3.67 3.58 3.78 3.77 3.71 3.52 3.64 3.85 3.83

Colleague Commitment 4.16 3.89 4.06 3.89 3.89 3.88 3.88 3.90 4.00 4.09 3.83 3.89 4.13 4.04 4.02 3.88 4.00 4.20 4.19

Staff & Equipment 3.60 3.11 3.47 3.10 3.57 3.38 3.28 3.54 4.00 3.46 3.26 3.46 3.51 3.42 3.62 3.17 3.29 3.60 3.67

Procedures & Training 3.74 3.68 3.77 3.74 3.75 3.72 3.69 3.83 3.50 3.73 3.68 3.93 3.71 3.73 3.80 3.63 3.60 3.74 3.84

Fatigue 2.99 2.38 2.95 2.48 3.55 3.09 3.24 3.21 2.86 2.49 2.90 2.91 2.80 3.16 2.53 2.66 3.04 2.95

Speaking up 3.91 3.79 3.79 3.80 3.57 3.64 3.40 3.77 3.00 3.87 3.69 3.63 3.91 3.83 3.73 3.63 3.82 3.99 3.90


2.78 2.25 2.93 2.38 3.39 2.89 3.05 3.18 3.18 2.68 2.41 2.78 2.73 2.63 2.92 2.38 2.62 2.83 2.64




Table 40 Means for dimensions by demographic groups (Management role; Training background)

Management role Training background

Dimension

Yes (flight operations and

training) Yes (safety

department)

Yes (other incl. Union/Compnay

Council) No Military Airline funded

cadetship

Self-funded cadetship, with

an airline (integrated)

training



Self-funded, self improver

(non-modular)

National flight school - state

funded Management Commitment to Safety

3.64 3.71 3.48 3.41 3.47 3.43 3.54 3.39 3.49 3.61 3.25 3.53

Collaboration & Involvement 3.63 3.70 3.63 3.60 3.62 3.68 3.66 3.52 3.53 3.65 3.27 3.63

Just Culture & Reporting 3.78 3.84 3.81 3.70 3.73 3.82 3.77 3.61 3.71 3.88 3.54 3.74

Communication & Learning 3.72 3.84 3.82 3.70 3.68 3.89 3.79 3.58 3.61 3.80 3.44 3.76

Risk Handling 3.82 3.77 3.80 3.76 3.77 3.80 3.85 3.72 3.75 3.85 3.52 3.80 Colleague Commitment 4.01 3.94 4.17 4.06 4.03 4.18 4.12 3.98 3.87 4.18 3.70 4.03

Staff Equipment 3.48 3.57 3.50 3.43 3.46 3.54 3.52 3.32 3.52 3.56 2.86 3.58

Procedures & Training 3.81 3.72 3.73 3.72 3.73 3.69 3.77 3.73 3.70 3.87 3.48 3.76

Fatigue 3.01 3.21 2.89 2.79 2.91 2.94 2.87 2.69 2.81 2.96 2.30 2.99

Speaking up 3.81 3.65 3.98 3.86 3.80 3.94 3.95 3.78 3.64 3.96 3.80 3.80 Perceived Organisational Support

2.89 2.98 2.75 2.62 2.77 2.64 2.71 2.60 2.74 2.71 2.48 2.75




Table 41 Means for dimensions by Nationality (for nationalities with =>30 respondents)

Dimension Austrians Belgians Croatians Danes Dutch Finns French citizens Germans Icelanders Irish Italians Luxembourgers Norwegians Portuguese Spaniards

St Lucians Swedes Swiss British


3.55 3.14 3.08 3.60 3.80 3.69 3.32 3.34 3.92 3.43 3.21 3.08 3.68 3.72 3.09 3.75 3.57 3.47 3.23




3.74 3.32 3.62 3.65 3.95 3.77 3.67 3.85 3.88 3.64 3.33 3.54 3.77 3.65 3.35 4.00 3.69 3.98 3.41

Risk Handling 3.80 3.68 3.54 3.86 4.05 3.93 3.74 3.77 3.89 3.76 3.59 3.73 3.81 3.79 3.45 4.00 3.79 3.81 3.61

Colleague Commitment 4.11 3.84 3.82 4.09 4.20 4.22 3.91 4.16 4.16 3.99 3.69 3.96 4.32 4.09 3.63 4.33 4.15 4.22 3.94

Staff Equipment 3.41 3.14 3.12 3.36 3.83 3.34 3.50 3.50 3.73 3.29 3.16 3.00 3.64 3.66 3.07 4.00 3.44 3.59 3.05


3.83 3.68 3.98 3.72 3.96 3.63 3.64 3.73 3.95 3.75 3.58 3.74 3.93 3.97 3.59 3.67 3.74 3.60 3.52

Fatigue 2.87 2.47 2.33 2.74 3.27 2.77 2.84 2.92 3.12 2.44 2.66 2.49 3.01 3.14 2.48 3.67 2.79 2.96 2.35

Speaking up 3.86 3.81 3.48 4.07 4.09 3.76 3.56 3.90 3.93 3.85 3.47 4.00 4.03 3.49 3.31 3.00 4.01 4.02 3.88


2.56 2.36 2.28 2.69 3.26 2.56 2.51 2.57 3.03 2.51 2.54 2.40 2.88 2.95 2.40 3.38 2.60 2.84 2.32




Table 42 Means for dimensions by country base (for countries with =>30 respondents)

Dimension Austria Belgium Croatia Denmark Estonia Finland France Germany Iceland Ireland Italy Luxembourg Netherlands Norway Portugal Spain Sweden Switzerland United

Kingdom Other Management Commitment to Safety

3.56 3.20 3.11 3.80 3.25 3.63 3.29 3.35 4.09 3.40 3.18 2.74 4.00 3.66 3.66 3.21 3.62 3.49 3.27 3.33

Collaboration & Involvement 3.49 3.41 3.34 3.76 3.56 3.83 3.52 3.61 3.81 3.65 3.35 3.43 3.97 3.77 3.59 3.30 3.71 3.80 3.41 3.41

Just Culture & Reporting 3.73 3.34 3.54 3.95 3.61 3.98 3.57 3.76 4.10 3.65 3.35 3.09 4.11 3.80 3.66 3.36 3.89 3.88 3.60 3.51


3.56 3.23 3.63 3.80 4.06 3.80 3.70 3.86 4.03 3.67 3.27 3.32 4.10 3.75 3.58 3.37 3.72 3.99 3.43 3.51

Risk Handling 3.84 3.66 3.53 3.94 3.67 3.92 3.72 3.77 4.01 3.77 3.65 3.63 4.13 3.79 3.80 3.56 3.79 3.78 3.63 3.54

Colleague Commitment 3.91 3.78 3.85 4.24 3.78 4.23 3.89 4.16 4.24 3.98 3.68 3.85 4.30 4.31 4.06 3.71 4.19 4.25 3.97 3.81

Staff Equipment 3.35 3.14 3.16 3.47 3.56 3.31 3.53 3.51 3.89 3.31 3.16 2.82 4.04 3.63 3.58 3.11 3.47 3.61 3.06 3.29


3.76 3.75 3.99 3.73 4.00 3.63 3.63 3.72 4.00 3.76 3.61 3.82 4.01 3.93 3.96 3.65 3.75 3.61 3.52 3.65

Fatigue 2.80 2.43 2.35 2.96 2.78 2.79 2.90 2.92 3.31 2.41 2.50 2.30 3.55 2.98 2.97 2.44 2.82 2.98 2.40 2.73

Speaking up 3.58 3.78 3.45 4.21 3.67 3.78 3.52 3.92 3.97 3.87 3.53 3.86 4.17 4.04 3.55 3.49 4.03 4.02 3.90 3.45


2.55 2.32 2.31 2.89 2.75 2.61 2.56 2.57 3.22 2.51 2.40 2.16 3.57 2.84 2.79 2.29 2.62 2.89 2.36 2.65

The means by aircraft type are not presented, as there were very few aircraft types for companies with more than 10 respondents.




7.3. Appendix 3 Favourable/Unfavourable Responses by Groups

This section shows the percentages of favourable and unfavourable responses for three of the groups that had most significant differences: company type, contract type and training background.

Table 43 Favourable/Unfavourable responses by Company type (excluding other category)

Items

Network Low cost Charter/leisure Cargo Aerial

work/ambulance/surveillance Helicopter General Aviation Business/VIP/State

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav

B01 My colleagues are committed to safety. 1.4% 2.5% 96.0% 3.5% 5.9% 90.6% 2.6% 5.0% 92.5% 3.8% 4.3% 91.9% 9.8% 9.8% 80.4% 8.0% 10.6% 81.4% 8.0% 12.0% 80.0% 5.2% 12.1% 82.8%

B02 Voicing concerns about safety is encouraged.

5.4% 9.5% 85.1% 14.6% 16.9% 68.5% 5.2% 13.4% 81.4% 11.2% 21.6% 67.2% 15.7% 15.7% 68.6% 10.7% 15.2% 74.1% 12.0% 13.3% 74.7% 13.0% 14.8% 72.2%

B03 We have sufficient staff to do our work safely.

20.0% 20.8% 59.2% 42.2% 24.3% 33.5% 26.9% 21.6% 51.5% 45.4% 24.3% 30.3% 21.6% 19.6% 58.8% 29.2% 17.7% 53.1% 31.1% 14.9% 54.1% 23.3% 20.7% 56.0%


10.8% 17.4% 71.8% 15.1% 23.6% 61.3% 9.2% 20.2% 70.6% 17.2% 24.2% 58.6% 20.0% 12.0% 68.0% 16.1% 20.5% 63.4% 17.3% 17.3% 65.3% 16.4% 14.7% 69.0%

B05 My direct manager is committed to safety. 9.0% 16.0% 75.0% 15.8% 20.8% 63.4% 10.9% 17.3% 71.8% 20.0% 28.9% 51.1% 21.6% 9.8% 68.6% 19.5% 17.7% 62.8% 14.7% 17.3% 68.0% 14.8% 11.3% 73.9%


33.1% 25.8% 41.1% 48.6% 23.7% 27.7% 28.5% 27.2% 44.3% 60.9% 23.5% 15.7% 23.5% 17.6% 58.8% 37.2% 18.6% 44.2% 28.4% 23.0% 48.6% 26.7% 23.3% 50.0%


3.7% 9.8% 86.6% 9.5% 15.1% 75.4% 4.4% 12.1% 83.5% 8.1% 15.2% 76.7% 9.8% 7.8% 82.4% 7.1% 14.2% 78.8% 8.0% 16.0% 76.0% 6.9% 12.9% 80.2%




Items





7.6% 13.3% 79.1% 19.4% 23.8% 56.8% 10.1% 14.2% 75.7% 21.9% 24.4% 53.7% 21.6% 9.8% 68.6% 29.2% 18.6% 52.2% 13.5% 23.0% 63.5% 14.7% 15.5% 69.8%

B09 People in this company share safety-related information.

6.8% 12.6% 80.5% 25.4% 19.0% 55.6% 8.1% 14.5% 77.3% 15.3% 20.7% 64.0% 9.8% 29.4% 60.8% 18.6% 15.0% 66.4% 13.3% 17.3% 69.3% 16.4% 18.1% 65.5%

B10 My direct manager takes action on the safety issues we raise.

12.6% 26.0% 61.5% 20.0% 31.6% 48.4% 13.7% 26.0% 60.3% 26.5% 35.2% 38.3% 18.0% 22.0% 60.0% 21.4% 21.4% 57.1% 16.0% 25.3% 58.7% 14.7% 19.8% 65.5%


10.8% 19.6% 69.6% 23.1% 18.8% 58.2% 14.4% 16.8% 68.8% 23.8% 27.1% 49.1% 7.8% 23.5% 68.6% 14.2% 25.7% 60.2% 20.5% 21.9% 57.5% 19.8% 15.5% 64.7%

B12 We get timely feedback on the safety issues we raise.

19.8% 29.5% 50.6% 34.8% 30.4% 34.8% 22.5% 29.0% 48.5% 34.7% 32.9% 32.4% 19.6% 31.4% 49.0% 25.7% 31.9% 42.5% 32.0% 30.7% 37.3% 24.1% 21.6% 54.3%

B13 My involvement in safety activities is sufficient.

5.9% 21.1% 72.9% 14.0% 31.4% 54.6% 7.2% 22.5% 70.3% 9.0% 29.8% 61.2% 11.8% 25.5% 62.7% 12.5% 16.1% 71.4% 10.7% 21.3% 68.0% 10.3% 25.9% 63.8%

B14r Pilots who raise safety issues are seen as troublemakers.

12.6% 15.4% 72.0% 25.5% 24.5% 50.0% 15.0% 17.9% 67.1% 22.4% 25.1% 52.6% 23.5% 9.8% 66.7% 33.6% 14.2% 52.2% 24.0% 14.7% 61.3% 25.0% 14.7% 60.3%


7.2% 12.6% 80.3% 11.1% 12.6% 76.3% 6.5% 12.2% 81.3% 13.0% 15.3% 71.7% 5.9% 9.8% 84.3% 10.7% 8.0% 81.3% 8.1% 10.8% 81.1% 1.7% 8.6% 89.7%


18.6% 24.5% 56.9% 34.0% 27.1% 38.9% 19.0% 26.0% 55.0% 38.3% 27.8% 33.9% 25.5% 17.6% 56.9% 26.5% 24.8% 48.7% 28.0% 22.7% 49.3% 19.1% 22.6% 58.3%




Items





24.9% 27.6% 47.5% 28.4% 28.6% 43.0% 22.3% 31.9% 45.9% 24.5% 34.8% 40.7% 27.5% 19.6% 52.9% 25.9% 32.1% 42.0% 24.0% 22.7% 53.3% 17.2% 26.7% 56.0%

B18 Safety is taken seriously in this company. 9.2% 17.3% 73.5% 15.9% 20.2% 63.9% 9.4% 17.3% 73.3% 18.2% 27.6% 54.3% 13.7% 19.6% 66.7% 15.9% 25.7% 58.4% 22.7% 18.7% 58.7% 14.7% 12.9% 72.4%


6.1% 10.8% 83.1% 14.4% 16.0% 69.6% 7.2% 14.7% 78.1% 15.2% 17.9% 66.8% 13.7% 15.7% 70.6% 14.2% 11.5% 74.3% 18.7% 16.0% 65.3% 12.9% 17.2% 69.8%


12.1% 27.2% 60.8% 20.6% 31.1% 48.3% 14.5% 28.2% 57.3% 24.2% 38.6% 37.2% 17.6% 17.6% 64.7% 20.4% 19.5% 60.2% 17.3% 22.7% 60.0% 15.7% 21.7% 62.6%


14.0% 25.4% 60.6% 27.6% 31.4% 41.0% 16.0% 26.2% 57.8% 24.8% 31.3% 43.8% 19.6% 27.5% 52.9% 20.5% 32.1% 47.3% 29.3% 22.7% 48.0% 19.1% 23.5% 57.4%


13.1% 18.9% 68.0% 43.6% 21.4% 35.0% 18.8% 21.1% 60.1% 29.4% 25.1% 45.5% 31.4% 17.6% 51.0% 16.8% 20.4% 62.8% 29.3% 17.3% 53.3% 25.2% 23.5% 51.3%


17.9% 15.1% 67.0% 27.1% 19.7% 53.3% 23.6% 16.1% 60.3% 26.5% 18.0% 55.5% 31.4% 15.7% 52.9% 32.7% 15.0% 52.2% 37.3% 24.0% 38.7% 28.7% 20.0% 51.3%


13.1% 23.5% 63.4% 14.9% 24.2% 61.0% 10.7% 24.7% 64.6% 25.8% 28.0% 46.2% 8.0% 24.0% 68.0% 7.1% 31.9% 61.1% 12.0% 18.7% 69.3% 7.9% 22.8% 69.3%




Items




B25 When I am unwell, I do not go to work. 9.1% 11.5% 79.4% 24.0% 14.9% 61.1% 11.8% 15.1% 73.2% 21.4% 17.6% 61.0% 16.0% 18.0% 66.0% 21.2% 15.9% 62.8% 21.3% 24.0% 54.7% 19.1% 25.2% 55.7%


3.1% 10.0% 86.9% 6.0% 14.3% 79.7% 3.1% 10.8% 86.0% 5.1% 11.2% 83.7% 6.0% 16.0% 78.0% 7.1% 14.2% 78.8% 9.3% 14.7% 76.0% .9% 7.8% 91.3%

C01 We have the resources needed to do our work safely.

10.8% 17.1% 72.1% 24.6% 19.6% 55.8% 15.1% 16.7% 68.2% 20.9% 21.4% 57.7% 10.6% 21.3% 68.1% 23.8% 16.2% 60.0% 21.9% 21.9% 56.3% 11.4% 19.0% 69.5%

C02 I read reports of incidents or occurrences that are relevant to our work.

2.1% 6.5% 91.4% 8.1% 10.5% 81.4% 2.5% 7.0% 90.5% 4.9% 6.5% 88.6% 6.4% 17.0% 76.6% 5.7% 3.8% 90.5% 7.8% 15.6% 76.6% 4.7% 6.6% 88.7%


21.2% 30.3% 48.5% 17.3% 23.8% 58.9% 18.5% 33.2% 48.3% 18.6% 27.1% 54.4% 29.8% 19.1% 51.1% 19.4% 29.1% 51.5% 31.3% 20.3% 48.4% 22.6% 31.1% 46.2%


10.4% 21.8% 67.8% 21.8% 21.6% 56.6% 11.2% 21.5% 67.2% 16.2% 25.3% 58.5% 6.4% 21.3% 72.3% 14.3% 22.9% 62.9% 20.3% 21.9% 57.8% 12.3% 20.8% 67.0%


14.1% 17.1% 68.9% 28.5% 23.8% 47.8% 17.1% 18.3% 64.7% 35.3% 22.7% 42.0% 14.9% 31.9% 53.2% 33.3% 19.0% 47.6% 25.0% 32.8% 42.2% 21.7% 23.6% 54.7%


4.5% 12.9% 82.6% 6.5% 18.1% 75.4% 3.9% 15.9% 80.2% 7.0% 16.3% 76.7% 6.4% 23.4% 70.2% 13.3% 29.5% 57.1% 23.4% 26.6% 50.0% 11.3% 21.7% 67.0%


18.6% 15.1% 66.3% 32.4% 12.2% 55.4% 17.1% 13.2% 69.7% 14.7% 18.1% 67.2% 6.4% 4.3% 89.4% 17.3% 16.3% 66.3% 14.1% 14.1% 71.9% 10.4% 14.2% 75.5%




Items





20.0% 23.6% 56.5% 24.7% 17.7% 57.5% 23.8% 20.2% 56.0% 21.0% 14.7% 64.3% 23.4% 14.9% 61.7% 23.8% 17.1% 59.0% 21.9% 14.1% 64.1% 23.6% 14.2% 62.3%


37.6% 25.8% 36.6% 36.1% 24.8% 39.1% 32.8% 25.8% 41.5% 33.2% 25.1% 41.8% 29.8% 25.5% 44.7% 27.6% 21.9% 50.5% 25.0% 20.3% 54.7% 25.5% 19.8% 54.7%


6.1% 9.5% 84.4% 8.1% 14.5% 77.4% 7.4% 14.5% 78.1% 8.6% 16.0% 75.3% 17.0% 14.9% 68.1% 21.0% 12.4% 66.7% 17.2% 20.3% 62.5% 15.1% 6.6% 78.3%


6.4% 15.7% 77.9% 11.9% 16.6% 71.5% 5.0% 17.6% 77.3% 8.6% 21.1% 70.3% 2.1% 10.6% 87.2% 2.9% 20.2% 76.9% 9.4% 14.1% 76.6% 5.7% 16.0% 78.3%


11.7% 20.3% 67.9% 8.9% 16.6% 74.5% 11.0% 21.7% 67.2% 29.5% 20.6% 49.9% 23.4% 23.4% 53.2% 26.7% 16.2% 57.1% 26.6% 17.2% 56.3% 15.1% 22.6% 62.3%

C13 I feel entirely confident to fly my aircraft.

2.0% 5.9% 92.2% 2.5% 5.7% 91.9% 2.7% 6.6% 90.7% 3.2% 6.7% 90.0% 6.4% 10.6% 83.0% 3.8% 9.5% 86.7% 10.9% 14.1% 75.0% 3.8% 10.4% 85.8%

C14 The SOPs associated with my work are appropriate to ensure safe operations.

5.5% 11.7% 82.8% 7.0% 12.3% 80.6% 4.1% 9.9% 86.0% 5.3% 8.6% 86.1% 12.8% 12.8% 74.5% 11.4% 17.1% 71.4% 11.1% 15.9% 73.0% 6.6% 17.9% 75.5%


4.4% 8.6% 87.0% 14.3% 16.3% 69.4% 5.2% 10.5% 84.3% 1.4% 73.5% 25.1% 0.0% 29.8% 70.2% 2.1% 36.8% 61.1% 3.3% 35.0% 61.7% 5.0% 24.0% 71.0%




Items





6.0% 11.1% 82.8% 6.3% 11.4% 82.2% 6.2% 11.2% 82.6% 4.4% 10.1% 85.5% 2.1% 12.8% 85.1% 5.7% 7.6% 86.7% 10.9% 12.5% 76.6% 3.8% 8.5% 87.7%

D01r Pilots in this company are often tired at work.

48.8% 27.1% 24.2% 75.6% 15.3% 9.0% 62.0% 18.9% 19.1% 82.5% 12.4% 5.1% 22.2% 28.9% 48.9% 34.3% 20.6% 45.1% 29.0% 32.3% 38.7% 35.6% 26.9% 37.5%

D02 First officers are willing to challenge Captains on their decision making.

10.2% 13.9% 75.9% 8.4% 19.5% 72.1% 10.8% 15.3% 73.9% 12.9% 22.7% 64.5% 18.6% 32.6% 48.8% 17.9% 31.6% 50.5% 24.1% 37.9% 37.9% 16.3% 25.0% 58.7%

D03r The company shows very little concern for my well-being.

36.4% 29.6% 34.0% 64.7% 22.5% 12.8% 36.4% 26.2% 37.4% 59.3% 21.5% 19.2% 33.3% 13.3% 53.3% 42.2% 22.5% 35.3% 32.3% 32.3% 35.5% 26.9% 25.0% 48.1%

D04 My national aviation authority manages safety reports well.

27.9% 47.0% 25.1% 30.2% 48.7% 21.1% 24.1% 48.9% 27.0% 35.5% 46.2% 18.3% 40.0% 37.8% 22.2% 38.6% 35.6% 25.7% 30.6% 32.3% 37.1% 21.6% 49.0% 29.4%

D05 The company takes pride in my accomplishments at work.

38.7% 37.5% 23.8% 59.9% 26.7% 13.4% 30.3% 41.5% 28.3% 57.2% 32.2% 10.6% 15.6% 20.0% 64.4% 35.6% 29.7% 34.7% 27.4% 33.9% 38.7% 19.4% 44.7% 35.9%

D06 I would feel comfortable to complete a fatigue report.

18.1% 15.0% 66.9% 40.7% 12.5% 46.8% 15.9% 12.1% 72.0% 25.0% 17.1% 57.9% 8.9% 17.8% 73.3% 31.4% 16.7% 52.0% 16.1% 17.7% 66.1% 17.5% 18.4% 64.1%

D07 My national aviation authority takes safety seriously.

20.4% 31.4% 48.2% 26.5% 31.7% 41.8% 18.1% 29.2% 52.6% 30.7% 36.6% 32.8% 31.1% 35.6% 33.3% 33.7% 19.8% 46.5% 25.8% 19.4% 54.8% 15.5% 27.2% 57.3%


4.7% 13.2% 82.1% 5.7% 19.1% 75.2% 7.4% 14.6% 78.0% 3.3% 13.6% 83.1% 6.7% 11.1% 82.2% 6.1% 14.1% 79.8% 8.5% 22.0% 69.5% 3.8% 15.4% 80.8%




Items




D09 The company values my contribution to its well-being.

37.3% 33.5% 29.2% 56.7% 27.2% 16.1% 26.9% 40.1% 33.0% 54.2% 30.4% 15.4% 22.2% 24.4% 53.3% 36.6% 26.7% 36.6% 24.6% 32.8% 42.6% 23.3% 27.2% 49.5%

D10 I feel this company returns the effort put in by its pilots.

54.3% 26.1% 19.7% 75.5% 16.1% 8.4% 41.7% 31.5% 26.8% 73.5% 17.6% 8.9% 37.8% 11.1% 51.1% 50.0% 19.6% 30.4% 37.1% 29.0% 33.9% 34.6% 30.8% 34.6%

D11 The company really cares about my wellbeing. 50.4% 30.1% 19.5% 75.5% 17.5% 7.0% 42.7% 32.2% 25.1% 69.6% 20.6% 9.8% 31.1% 24.4% 44.4% 47.1% 25.5% 27.5% 35.5% 33.9% 30.6% 29.8% 38.5% 31.7%

D12 The issue of fatigue is taken seriously by this company.

44.6% 29.8% 25.6% 65.3% 20.2% 14.5% 44.2% 30.4% 25.3% 62.1% 22.5% 15.5% 24.4% 28.9% 46.7% 38.6% 21.8% 39.6% 33.9% 24.2% 41.9% 26.9% 28.8% 44.2%

D13r The company fails to appreciate any extra effort from me.

50.6% 26.6% 22.8% 63.9% 18.4% 17.7% 43.2% 31.7% 25.0% 57.2% 21.0% 21.7% 28.9% 22.2% 48.9% 47.5% 21.8% 30.7% 38.7% 32.3% 29.0% 31.7% 27.9% 40.4%

D14 The company cares about my general satisfaction at work.

50.8% 30.2% 19.0% 71.3% 20.4% 8.3% 38.9% 34.2% 27.0% 68.9% 21.0% 10.0% 24.4% 31.1% 44.4% 44.1% 24.5% 31.4% 37.1% 32.3% 30.6% 31.7% 31.7% 36.5%

D15r Even if I did the best job possible, the company would fail to notice.

50.1% 26.9% 23.1% 66.2% 19.7% 14.1% 39.3% 30.8% 29.9% 64.3% 20.8% 15.0% 31.1% 17.8% 51.1% 41.6% 26.7% 31.7% 37.1% 27.4% 35.5% 29.8% 27.9% 42.3%

D16r The company would ignore any complaint from me.

14.9% 28.6% 56.5% 32.1% 33.3% 34.6% 16.9% 24.3% 58.8% 25.9% 33.2% 40.9% 15.6% 22.2% 62.2% 19.6% 24.5% 55.9% 19.4% 25.8% 54.8% 14.4% 20.2% 65.4%

D17 I feel fully supported by my company if I report unfit to fly.

24.5% 25.8% 49.7% 46.1% 26.4% 27.6% 29.9% 28.3% 41.8% 49.8% 23.7% 26.5% 13.3% 17.8% 68.9% 31.4% 20.6% 48.0% 33.9% 24.2% 41.9% 24.0% 19.2% 56.7%




Table 44 Favourable/Unfavourable responses by Contract type (excluding other category)

Items

Contract type

Typical contract Atypical contract

Unfavourable Neutral Favourable Unfavourable Neutral Favourable

B01 My colleagues are committed to safety. 2.2% 3.4% 94.5% 4.6% 9.3% 86.1%

B02 Voicing concerns about safety is encouraged. 7.2% 12.1% 80.7% 17.3% 17.3% 65.3%


27.2% 21.4% 51.3% 32.8% 24.4% 42.8%


11.9% 19.1% 69.0% 16.4% 22.7% 60.9%

B05 My direct manager is committed to safety.

11.7% 17.9% 70.4% 13.1% 19.3% 67.6%


38.2% 25.2% 36.6% 38.1% 23.6% 38.3%


4.9% 10.8% 84.3% 10.4% 19.3% 70.3%


10.9% 15.8% 73.3% 22.2% 24.6% 53.2%


11.1% 14.6% 74.3% 22.5% 19.7% 57.8%

B10 My direct manager takes action on the safety issues we raise.

15.3% 28.0% 56.8% 17.8% 26.2% 56.0%


14.6% 20.2% 65.2% 19.2% 17.0% 63.8%




Items

Contract type



B12 We get timely feedback on the safety issues we raise. 24.1% 30.0% 45.9% 31.5% 28.6% 40.0%


7.8% 23.4% 68.8% 13.5% 31.1% 55.4%


15.8% 18.0% 66.2% 28.7% 20.4% 50.9%


8.1% 12.5% 79.4% 10.9% 12.6% 76.5%


23.0% 25.4% 51.6% 30.6% 25.2% 44.2%


26.0% 28.7% 45.2% 20.3% 27.7% 51.9%

B18 Safety is taken seriously in this company. 11.5% 19.1% 69.4% 13.5% 16.4% 70.1%


8.7% 12.7% 78.6% 12.9% 15.2% 71.9%


15.0% 28.6% 56.4% 18.0% 28.7% 53.2%


17.5% 27.3% 55.2% 26.0% 29.4% 44.6%


20.5% 19.9% 59.6% 38.8% 21.2% 40.0%




Items

Contract type


Unfavourable Neutral Favourable Unfavourable Neutral Favourable B23r There are people who I do not want to work with because of their negative (e.g. loose, careless) attitude to safety.

19.9% 16.5% 63.5% 36.4% 16.9% 46.8%


14.0% 24.3% 61.7% 14.3% 22.1% 63.6%

B25 When I am unwell, I do not go to work. 12.0% 13.0% 75.0% 31.1% 16.6% 52.3%


3.6% 10.5% 85.9% 7.5% 17.5% 75.1%

C01 We have the resources needed to do our work safely. 14.6% 18.0% 67.3% 21.5% 18.3% 60.2%


3.7% 7.2% 89.1% 6.3% 11.2% 82.5%


20.2% 29.1% 50.7% 19.6% 23.8% 56.6%


13.2% 21.9% 64.9% 18.3% 22.3% 59.4%


18.3% 18.7% 63.0% 30.2% 26.1% 43.7%


5.1% 14.2% 80.7% 8.7% 22.6% 68.7%


19.3% 14.4% 66.3% 38.2% 13.9% 47.9%




Items

Contract type




22.2% 21.5% 56.4% 17.3% 16.1% 66.5%


37.1% 25.6% 37.2% 27.6% 22.0% 50.4%


6.8% 11.0% 82.2% 11.8% 16.3% 71.9%


7.3% 16.3% 76.5% 11.4% 18.0% 70.6%


12.6% 19.8% 67.6% 13.2% 17.6% 69.2%

C13 I feel entirely confident to fly my aircraft. 2.2% 5.7% 92.1% 3.6% 10.1% 86.3%


5.6% 11.6% 82.8% 8.9% 12.7% 78.5%


5.4% 14.1% 80.5% 17.2% 23.7% 59.1%


6.1% 10.9% 82.9% 5.0% 12.0% 83.1%

D01r Pilots in this company are often tired at work. 56.7% 23.0% 20.3% 64.5% 19.9% 15.6%


10.2% 16.2% 73.6% 12.0% 21.1% 66.9%




Items

Contract type




42.6% 27.7% 29.7% 61.0% 19.9% 19.1%


29.6% 47.1% 23.4% 23.5% 47.6% 28.9%


42.6% 36.0% 21.4% 54.3% 23.5% 22.1%


21.4% 14.5% 64.1% 45.1% 13.2% 41.7%


22.7% 31.4% 45.8% 22.2% 30.2% 47.5%


4.5% 14.5% 81.0% 10.2% 17.8% 71.9%

D09 The company values my contribution to its well-being. 40.8% 32.8% 26.4% 50.9% 25.4% 23.7%


58.2% 24.2% 17.6% 66.3% 17.2% 16.5%

D11 The company really cares about my wellbeing. 55.3% 27.4% 17.3% 66.4% 19.9% 13.7%


49.4% 27.4% 23.2% 56.4% 22.0% 21.6%


52.7% 25.1% 22.2% 56.5% 20.0% 23.4%




Items

Contract type




54.4% 28.0% 17.6% 63.0% 22.8% 14.2%


52.8% 25.3% 21.9% 57.8% 22.6% 19.6%


18.3% 29.5% 52.2% 33.2% 29.3% 37.4%


29.9% 26.1% 44.0% 47.8% 22.9% 29.3%




Table 45 Favourable/Unfavourable responses by Training background (excluding other category)

Items

Training background

Military Airline funded cadetship Self-funded cadetship, with

an airline (integrated) training Self-funded, modular training University - State funded Self-funded, self improver

(non-modular) National flight school - state

funded

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav B01 My colleagues are committed to safety.

2.8% 5.4% 91.8% 1.4% 1.4% 97.2% 2.2% 2.3% 95.5% 2.9% 5.7% 91.4% 2.4% 9.5% 88.1% 18.2% 4.5% 77.3% 2.0% 2.7% 95.3%

B02 Voicing concerns about safety is encouraged.

7.7% 13.7% 78.6% 4.9% 10.3% 84.8% 7.8% 10.2% 82.0% 10.7% 14.7% 74.7% 7.1% 11.9% 81.0% 4.5% 13.6% 81.8% 7.4% 11.1% 81.4%


24.8% 20.9% 54.2% 22.6% 23.2% 54.2% 26.7% 20.5% 52.8% 33.3% 21.7% 45.1% 16.7% 26.2% 57.1% 59.1% 13.6% 27.3% 15.9% 22.6% 61.5%


13.0% 20.3% 66.8% 10.9% 18.7% 70.4% 9.8% 19.4% 70.8% 13.7% 19.9% 66.3% 9.5% 7.1% 83.3% 22.7% 22.7% 54.5% 14.9% 19.3% 65.9%

B05 My direct manager is committed to safety.

12.0% 16.9% 71.1% 9.3% 18.7% 72.0% 10.6% 15.7% 73.8% 14.1% 18.8% 67.1% 11.9% 14.3% 73.8% 9.1% 31.8% 59.1% 8.8% 17.9% 73.3%


35.1% 24.6% 40.3% 40.2% 28.8% 31.1% 34.0% 24.4% 41.6% 39.6% 23.3% 37.1% 31.0% 21.4% 47.6% 54.5% 27.3% 18.2% 35.5% 27.4% 37.2%


5.3% 11.0% 83.8% 3.2% 9.8% 87.0% 4.2% 11.3% 84.5% 7.5% 13.3% 79.2% 0.0% 2.4% 97.6% 9.1% 9.1% 81.8% 5.8% 11.5% 82.7%


12.1% 17.2% 70.7% 6.5% 13.5% 80.0% 11.1% 15.3% 73.6% 15.7% 19.3% 65.0% 11.9% 9.5% 78.6% 22.7% 9.1% 68.2% 9.8% 15.5% 74.7%


14.4% 15.9% 69.8% 5.2% 13.3% 81.5% 10.6% 13.3% 76.2% 16.8% 16.4% 66.8% 7.1% 19.0% 73.8% 27.3% 9.1% 63.6% 9.5% 15.9% 74.7%




Items

Training background




funded

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav B10 My direct manager takes action on the safety issues we raise.

16.2% 25.7% 58.2% 12.9% 31.3% 55.8% 14.0% 24.4% 61.7% 17.9% 27.2% 54.8% 11.9% 26.2% 61.9% 18.2% 40.9% 40.9% 11.8% 31.1% 57.1%


15.0% 21.1% 63.9% 11.0% 19.2% 69.8% 13.9% 16.9% 69.1% 18.1% 20.7% 61.1% 16.7% 16.7% 66.7% 18.2% 22.7% 59.1% 11.8% 20.3% 67.9%

B12 We get timely feedback on the safety issues we raise.

24.2% 27.7% 48.2% 21.6% 31.9% 46.4% 23.8% 27.9% 48.3% 28.1% 29.2% 42.7% 14.3% 26.2% 59.5% 45.5% 36.4% 18.2% 20.3% 33.4% 46.3%


8.6% 22.5% 68.9% 5.9% 22.5% 71.6% 7.2% 22.5% 70.3% 10.4% 26.5% 63.1% 7.1% 14.3% 78.6% 27.3% 36.4% 36.4% 7.1% 23.3% 69.6%


18.8% 17.4% 63.9% 11.5% 17.0% 71.5% 15.3% 16.7% 67.9% 21.4% 19.8% 58.8% 16.7% 19.0% 64.3% 22.7% 13.6% 63.6% 11.8% 18.2% 69.9%


6.7% 10.8% 82.5% 8.2% 15.5% 76.3% 7.6% 12.0% 80.4% 9.2% 11.8% 79.0% 4.8% 2.4% 92.9% 4.5% 4.5% 90.9% 7.8% 11.6% 80.6%


23.1% 26.0% 50.9% 20.4% 27.6% 52.0% 19.6% 24.5% 55.9% 28.0% 24.4% 47.6% 16.7% 26.2% 57.1% 36.4% 18.2% 45.5% 19.6% 24.0% 56.4%


24.7% 29.5% 45.8% 30.3% 30.5% 39.2% 21.8% 25.5% 52.7% 24.2% 28.1% 47.7% 16.7% 40.5% 42.9% 27.3% 36.4% 36.4% 25.3% 30.1% 44.6%

B18 Safety is taken seriously in this company.

13.6% 19.9% 66.5% 8.8% 20.4% 70.8% 10.3% 13.8% 75.8% 13.9% 19.6% 66.6% 4.8% 14.3% 81.0% 18.2% 22.7% 59.1% 9.1% 16.2% 74.7%




Items

Training background




funded

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav B19 We learn lessons from safety-related incident or occurrence investigations.

10.7% 14.6% 74.7% 5.2% 11.1% 83.7% 6.7% 11.1% 82.2% 12.2% 14.5% 73.2% 7.1% 7.1% 85.7% 18.2% 18.2% 63.6% 6.1% 12.8% 81.1%


15.4% 27.1% 57.4% 12.2% 31.9% 55.9% 13.2% 27.3% 59.5% 18.1% 28.0% 53.9% 11.9% 26.2% 61.9% 4.5% 40.9% 54.5% 12.9% 24.4% 62.7%


20.0% 26.6% 53.4% 13.5% 27.4% 59.1% 15.9% 24.7% 59.4% 22.3% 28.3% 49.4% 14.3% 23.8% 61.9% 31.8% 27.3% 40.9% 13.9% 30.5% 55.6%


21.3% 22.0% 56.7% 11.5% 17.9% 70.6% 21.9% 18.5% 59.6% 29.1% 21.7% 49.2% 23.8% 7.1% 69.0% 45.5% 13.6% 40.9% 21.7% 19.0% 59.3%


20.3% 16.2% 63.5% 17.0% 14.3% 68.7% 22.8% 14.7% 62.5% 24.2% 18.5% 57.3% 23.8% 14.3% 61.9% 22.7% 22.7% 54.5% 22.6% 18.9% 58.4%


12.8% 26.0% 61.2% 15.2% 23.3% 61.6% 13.2% 19.8% 67.0% 14.2% 25.3% 60.5% 16.7% 23.8% 59.5% 18.2% 36.4% 45.5% 11.1% 25.3% 63.5%

B25 When I am unwell, I do not go to work.

12.6% 13.4% 74.0% 8.4% 12.5% 79.1% 13.8% 14.0% 72.2% 17.9% 13.7% 68.4% 14.3% 14.3% 71.4% 14.3% 19.0% 66.7% 12.2% 14.9% 72.9%


3.3% 8.7% 88.0% 2.4% 8.5% 89.1% 3.7% 11.5% 84.8% 5.1% 12.9% 82.0% 2.4% 11.9% 85.7% 0.0% 9.1% 90.9% 4.7% 17.3% 78.0%




Items

Training background




funded

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav C01 We have the resources needed to do our work safely.

15.3% 17.5% 67.2% 11.4% 18.3% 70.2% 15.2% 14.8% 70.0% 18.3% 19.0% 62.6% 9.8% 19.5% 70.7% 31.8% 27.3% 40.9% 11.0% 18.5% 70.5%


5.6% 9.8% 84.6% 1.6% 3.8% 94.6% 3.9% 6.7% 89.4% 4.8% 9.6% 85.6% 0.0% 9.8% 90.2% 4.5% 4.5% 90.9% 4.3% 7.5% 88.3%


20.6% 24.8% 54.7% 17.7% 33.3% 49.0% 22.0% 30.6% 47.4% 19.8% 26.2% 54.0% 19.5% 39.0% 41.5% 22.7% 13.6% 63.6% 25.2% 29.9% 45.0%


12.9% 22.4% 64.7% 8.6% 22.7% 68.8% 11.9% 20.7% 67.4% 17.5% 22.1% 60.4% 19.5% 9.8% 70.7% 27.3% 27.3% 45.5% 13.9% 21.0% 65.1%


16.9% 21.5% 61.6% 12.2% 17.0% 70.8% 17.9% 18.7% 63.4% 25.4% 20.7% 54.0% 24.4% 14.6% 61.0% 27.3% 27.3% 45.5% 17.1% 17.4% 65.5%


5.2% 16.5% 78.3% 3.2% 11.4% 85.4% 4.4% 13.4% 82.2% 7.5% 17.7% 74.8% 2.4% 12.2% 85.4% 9.1% 13.6% 77.3% 5.0% 14.2% 80.8%


19.9% 16.3% 63.8% 20.7% 16.9% 62.4% 22.0% 12.6% 65.3% 22.1% 13.0% 65.0% 9.8% 17.1% 73.2% 54.5% 9.1% 36.4% 16.7% 16.0% 67.3%


21.0% 22.7% 56.2% 22.2% 24.2% 53.5% 20.9% 19.5% 59.6% 22.6% 19.1% 58.3% 19.5% 17.1% 63.4% 27.3% 18.2% 54.5% 15.7% 22.8% 61.6%




Items

Training background




funded

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav C09 Adequate training is provided when new systems and procedures are introduced.

36.4% 25.1% 38.5% 42.4% 27.4% 30.1% 31.7% 23.4% 44.9% 34.3% 24.9% 40.8% 31.7% 14.6% 53.7% 50.0% 27.3% 22.7% 34.2% 25.3% 40.6%


6.8% 12.7% 80.5% 5.3% 9.6% 85.1% 6.1% 10.0% 83.9% 9.2% 13.3% 77.5% 2.4% 7.3% 90.2% 9.1% 18.2% 72.7% 7.5% 7.9% 84.6%


8.4% 22.5% 69.2% 5.4% 15.9% 78.7% 7.4% 14.0% 78.6% 8.8% 16.3% 74.9% 7.3% 9.8% 82.9% 4.5% 13.6% 81.8% 8.6% 17.1% 74.3%


13.6% 19.7% 66.7% 12.0% 21.7% 66.4% 10.9% 18.4% 70.7% 13.1% 18.5% 68.4% 12.2% 9.8% 78.0% 9.1% 4.5% 86.4% 18.9% 24.2% 56.9%

C13 I feel entirely confident to fly my aircraft. 1.8% 5.8% 92.4% 1.7% 5.7% 92.6% 2.3% 4.9% 92.8% 3.1% 7.0% 89.9% 2.4% 0.0% 97.6% 4.5% 9.1% 86.4% .7% 6.0% 93.2%


7.3% 11.6% 81.1% 5.5% 13.9% 80.6% 4.6% 10.7% 84.7% 6.5% 11.0% 82.4% 4.9% 12.2% 82.9% 0.0% 22.7% 77.3% 4.3% 9.6% 86.1%


4.1% 15.6% 80.3% 4.1% 10.8% 85.1% 6.3% 14.3% 79.4% 9.2% 17.5% 73.2% 4.9% 7.3% 87.8% 9.1% 31.8% 59.1% 4.3% 15.6% 80.1%




Items

Training background




funded

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav C16 I have sufficient training to understand the procedures associated with my work.

6.0% 10.7% 83.3% 6.2% 12.2% 81.6% 5.0% 10.0% 85.0% 6.2% 11.1% 82.7% 7.3% 0.0% 92.7% 9.1% 18.2% 72.7% 6.4% 9.6% 83.9%

D01r Pilots in this company are often tired at work.

55.5% 23.0% 21.6% 47.2% 28.8% 24.0% 57.8% 18.2% 24.0% 65.0% 20.1% 14.9% 56.1% 26.8% 17.1% 81.8% 13.6% 4.5% 47.3% 29.7% 22.9%


13.1% 17.3% 69.6% 9.1% 14.2% 76.6% 7.2% 13.5% 79.3% 11.0% 19.4% 69.6% 4.9% 12.2% 82.9% 4.5% 22.7% 72.7% 15.8% 14.7% 69.4%


41.5% 28.3% 30.2% 37.0% 32.9% 30.0% 43.5% 23.2% 33.3% 50.5% 24.2% 25.3% 51.2% 26.8% 22.0% 40.9% 31.8% 27.3% 35.5% 30.8% 33.7%


32.8% 44.9% 22.3% 25.9% 48.5% 25.6% 22.8% 48.8% 28.4% 31.7% 45.8% 22.5% 27.5% 57.5% 15.0% 36.4% 40.9% 22.7% 29.7% 51.1% 19.2%


35.5% 40.2% 24.3% 44.9% 37.7% 17.3% 44.4% 31.4% 24.2% 45.0% 32.8% 22.2% 39.0% 39.0% 22.0% 50.0% 36.4% 13.6% 42.8% 33.1% 24.1%


20.2% 15.1% 64.7% 18.5% 18.1% 63.5% 25.4% 11.8% 62.8% 27.5% 13.2% 59.4% 24.4% 12.2% 63.4% 36.4% 18.2% 45.5% 20.8% 12.5% 66.7%


23.7% 31.3% 45.0% 17.8% 31.2% 51.0% 20.1% 28.8% 51.1% 26.4% 31.8% 41.8% 31.7% 31.7% 36.6% 31.8% 40.9% 27.3% 17.7% 33.2% 49.1%


5.9% 16.7% 77.3% 3.5% 11.5% 85.0% 3.9% 13.8% 82.4% 6.5% 16.6% 76.9% 7.3% 14.6% 78.0% 4.5% 22.7% 72.7% 4.7% 15.1% 80.2%




Items

Training background




funded

Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav Unfav Neut. Fav D09 The company values my contribution to its well-being.

33.6% 37.7% 28.6% 43.7% 35.9% 20.4% 40.3% 27.0% 32.7% 43.5% 30.3% 26.2% 35.0% 37.5% 27.5% 36.4% 45.5% 18.2% 44.8% 29.7% 25.4%


52.8% 26.7% 20.5% 61.4% 26.8% 11.8% 57.0% 20.0% 23.0% 60.3% 22.1% 17.7% 58.5% 14.6% 26.8% 63.6% 22.7% 13.6% 58.1% 23.7% 18.3%

D11 The company really cares about my wellbeing. 51.1% 31.0% 17.9% 56.9% 30.5% 12.6% 54.6% 23.0% 22.4% 58.5% 24.4% 17.0% 65.9% 22.0% 12.2% 63.6% 27.3% 9.1% 54.8% 26.5% 18.6%


45.4% 28.8% 25.9% 48.6% 30.0% 21.4% 45.9% 25.7% 28.4% 54.6% 24.2% 21.2% 39.0% 34.1% 26.8% 72.7% 13.6% 13.6% 43.7% 31.5% 24.7%


46.9% 28.1% 25.0% 56.8% 25.6% 17.6% 52.0% 23.4% 24.7% 52.7% 23.8% 23.4% 48.8% 26.8% 24.4% 72.7% 18.2% 9.1% 53.0% 23.3% 23.7%


49.5% 31.1% 19.4% 57.1% 31.4% 11.5% 52.7% 25.2% 22.1% 57.0% 25.4% 17.6% 53.7% 29.3% 17.1% 63.6% 31.8% 4.5% 52.0% 25.4% 22.6%


48.4% 28.8% 22.8% 55.5% 25.6% 18.9% 51.7% 22.6% 25.7% 53.9% 24.8% 21.3% 56.1% 24.4% 19.5% 63.6% 27.3% 9.1% 50.9% 24.4% 24.7%


18.4% 30.0% 51.6% 15.4% 30.9% 53.7% 19.2% 25.6% 55.2% 23.4% 29.9% 46.8% 17.1% 29.3% 53.7% 22.7% 36.4% 40.9% 19.4% 28.0% 52.7%


25.2% 26.4% 48.4% 26.6% 28.5% 44.9% 31.4% 25.2% 43.5% 37.9% 24.0% 38.1% 24.4% 26.8% 48.8% 18.2% 31.8% 50.0% 19.4% 25.1% 55.6%

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